Input device, element data configuration method, and program

ABSTRACT

A data configuration process is repeatedly performed at least twice, and a sum of a value obtained by multiplying a difference between a first temporary value (PA j   t=1 ) of element data obtained by the first data configuration process and a second temporary value (PA j   t=2 ) of the element data obtained by the second data configuration process by a predetermined proportionality coefficient γ and the first temporary value (PA j   t=1 ) is calculated for each of M sections A 1  to A M  as values approximated to a convergence value of the element data. By this, the number of times the data configuration process is repeatedly performed is considerably reduced when compared with a case where a convergence value of element data is obtained by repeatedly performing the data configuration process a number of times.

CLAIM OF PRIORITY

This application is a Continuation of International Application No.PCT/JP2018/008555 filed on Mar. 6, 2018, which claims benefit ofJapanese Patent Application No. 2017-072051 filed on Mar. 31, 2017. Theentire contents of each application noted above is incorporated hereinby reference.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention relates to an input device which is used to inputinformation in an information apparatus, such as a computer or asmartphone, and particularly, relates to an input device which is usedto specify a region to which an object, such as a finger or a pen,approaches an operation plane, and which inputs information based on thespecified region.

2. Description of the Related Art

Input devices, such as a touch pad or a touch panel, which are used toinput information by specifying a contact position of a finger inaccordance with a change of an electrostatic capacitance generallyemploy an image sensing method for simultaneously detecting a pluralityof contact positions.

Furthermore, examples of a method for detecting a change of anelectrostatic capacitance include a mutual capacitance method fordetecting a change of an electrostatic capacitance between twoelectrodes and a self-capacitance method for detecting an electrostaticcapacitance between an electrode and the ground. In a case where ahovering function of detecting an operation of a finger separated froman operation plane is to be realized, a sensor of the self-capacitancemethod which has high detection sensitivity of an electrostaticcapacitance is advantageously used.

However, in a general self-capacitance type sensor, one electrodedetects an electrostatic capacitance only in one location, andtherefore, if this sensor is employed in an image sensing method, thehigher a resolution is, the larger the number of electrodes is. Toaddress this problem, according to International Publication No.WO2016/021356, an input device which configures electrostaticcapacitance data (element data) in each of a plurality of sections seton an operation plane based on electrostatic capacitance data (detectiondata) detected by a smaller number of electrodes than a number ofsections is disclosed.

SUMMARY OF THE INVENTION

In the input device disclosed in International Publication No.WO2016/021356, a data configuration process is repeatedly performed toconfigure m pieces of element data by using n pieces of detection data(m>n). In each data configuration process, temporary detection data iscalculated by using temporary element data, and the temporary elementdata is corrected based on a comparison between the temporary detectiondata and actual detection data. As the number of repeating times of thedata configuration process is increased, accuracy of configured elementdata is improved. However, in terms of reduction of a calculation load,it is desirable that the number of repeating times of the dataconfiguration process is reduced.

The present invention is made in consideration of such a situation, andprovides an input device capable of configuring element data indicatingdegrees of proximity of an object in a plurality of sections on anoperation plane by a simple calculation using a smaller number ofdetection data than a number of the sections, a method for configuringthe element data, and a program.

Solution to Problem

According to a first aspect of the present invention, an input devicewhich inputs information corresponding to proximity of an object to anoperation plane is provided. The input device includes a sensor unitconfigured to detect a degree of proximity of the object in one or moredetection regions on the operation plane, generate one or more pieces ofdetection data corresponding to a result of the detection for eachdetection region, and generate N pieces of detection data as a whole,and an element data configuration unit configured to configure, based onthe N pieces of detection data, M pieces of element data indicatingdegrees of proximity of the object in each of M sections (M is a naturalnumber larger than N) which virtually divide the operation plane. Eachof the M sections has at least one overlapping portion which overlapswith the detection region. Each of the M pieces of element data is a sumof partial element data distributed to each of the N pieces of detectiondata in predetermined rates. Each of the N pieces of detection data isapproximated to a sum of the partial element data individuallydistributed from each of the M pieces of element data in thepredetermined rates. The element data configuration unit calculates eachof temporary values of the N pieces of detection data as sums of thepartial element data distributed from each of temporary values of the Mpieces of element data in the predetermined rates and repeatedlyperforms a data configuration process of correcting the temporary valuesof the M pieces of element data at least twice based on the Npredetermined rates set for the individual M pieces of element data sothat the calculated temporary values of the N pieces of detection dataare approximated to the N pieces of detection data. Further, the elementdata configuration unit calculates, based on two temporary valuesobtained by the data configuration process performed twice on each ofthe M pieces of element data, a coefficient having an absolute valuewhich becomes small as a difference between the two temporary values inthe element data becomes large, and calculates, with respect to each ofthe M sections, a sum of a value obtained by multiplying a differencebetween a first temporary value of the element data obtained by thefirst data configuration process and a second temporary value of theelement data obtained by the second data configuration process by thecoefficient and the first temporary value as an estimation value of theelement data obtained by repeatedly performing the data configurationprocess.

With this configuration, each of the M sections which virtually dividethe operation plane has an overlapping portion which overlaps with atleast one detection region, and the sensor unit generates at least onepiece of detection data for each detection region. Therefore, at leastone piece of detection data indicating a degree of proximity of theobject is generated for each of the M sections.

Furthermore, each of the M pieces of element data is a sum of partialelement data distributed to each of the N pieces of detection data inpredetermined rates, and each of the N pieces of detection data isapproximated to a sum of the partial element data distributed in thepredetermined rates from each of the M pieces of element data.Specifically, conversion from the M pieces of element data into the Npieces of detection data is specified in accordance with the Npredetermined rates set to each of the M pieces of element data.

In the data configuration process, temporary values of the N pieces ofdetection data are individually calculated as a sum of the partialelement data distributed in the predetermined rates from the individualtemporary values of the M pieces of element data. Furthermore, temporaryvalues of the M pieces of element data are corrected based on the Npredetermined rates set for each of the M pieces of element data so thatthe calculated temporary values of the N pieces of detection data becomeclose to the N pieces of detection data. By repeatedly performing thedata configuration process a number of times, a convergence value of theelement data suitable for the N pieces of detection data may beobtained.

However, the element data configuration unit repeatedly performs thedata configuration process at least twice so as to calculate a sum of avalue obtained by multiplying a difference between a first temporaryvalue of the element data obtained by the first data configurationprocess and a second temporary value of the element data obtained by thesecond data configuration process by the coefficient and the firsttemporary value as an estimation value of the element data obtained byrepeatedly performing the data configuration process. Accordingly,calculation is simplified compared with a case where a convergence valueof the element data is obtained by repeatedly performing the dataconfiguration process a number of times.

Furthermore, the estimation value of the element data obtained as a sumof the value obtained by multiplying the difference between the firsttemporary value and the second temporary value by the coefficient andthe first temporary value has a certain degree of error relative to theconvergence value of the element data obtained by repeatedly performingthe data configuration process a number of times. The coefficient whichminimizes the error has a tendency to have an absolute value whichbecomes smaller as the difference between the two temporary valuesbecomes larger in the element data. Accordingly, by calculating thecoefficient such that the absolute value becomes small as the differencebetween the two temporary values becomes large in each of the elementdata based on the two temporary values obtained by the dataconfiguration process performed twice on each of the M pieces of elementdata, the error may be reduced compared with a case where thecoefficient is set to a fixed value.

Preferably, the element data configuration unit may calculate anevaluation value corresponding to a difference degree between the twotemporary values of each of the M pieces of element data and obtain avalue of a predetermined function using the evaluation value as avariable as the coefficient.

By this, the optimum coefficient corresponding to a difference degree ofthe two temporary values in each of the M pieces of element data may beobtained.

Preferably, the evaluation value may be increased as the differencedegree of the two temporary values of each of the M pieces of elementdata is increased. In the predetermined function, an absolute value of aderivative in a range in which the evaluation value is smaller than athreshold value may be larger than an absolute value of a derivative ina range in which the evaluation value is larger than the thresholdvalue.

As a distance between the objects approaching the operation plane 11 isreduced, a difference degree of the two temporary values in each of theM pieces of element data P tends to be small. Furthermore, when thedistance between the objects is short, a boundary between the objectshas a tendency to be clarified by increasing the coefficient. Therefore,an absolute value of the derivative in the range in which the evaluationvalue is smaller than the threshold value is made larger than anabsolute value of the derivative in the range in which the evaluationvalue is larger than the threshold value, and thereby, the coefficientis easily increased when the evaluation value is reduced since thedistance between the objects is reduced, and accordingly, the boundarybetween the objects may be clarified.

Preferably, the difference degree may be an absolute value of adifference between the two temporary values. The element dataconfiguration unit may calculate the evaluation value according to a sumof the M difference degrees corresponding to the M pieces of elementdata. In this case, the predetermined function may be a linear functionhaving a negative inclination. Furthermore, the evaluation value may beincreased as the difference degree of the two temporary values of eachof the M pieces of element data is increased. In the predeterminedfunction, an absolute value of an inclination in a range in which theevaluation value is smaller than a threshold value may be larger than anabsolute value of an inclination in a range in which the evaluationvalue is larger than the threshold value.

As the distance between the objects approaching the operation plane isreduced, the difference degree of the two temporary values in each ofthe M pieces of element data tends to be small. Furthermore, when thedistance between the objects is short, the boundary between the objectstends to be clarified by increasing the coefficient. Accordingly, anabsolute value of the inclination in the range in which the evaluationvalue is smaller than the threshold value is made larger than anabsolute value of the inclination in the range in which the evaluationvalue is larger than the threshold value, and thereby, the coefficientis easily increased when the evaluation value is reduced since thedistance between the objects is reduced, and accordingly, the boundarybetween the objects is more likely to be clarified.

Preferably, the evaluation value may be changed in accordance with therelative positional relationship between the plurality of objectsapproaching the operation plane.

Preferably, the two temporary values may be the first and secondtemporary values.

Accordingly, calculation is simplified as compared with the case wherethe two temporary values are different from the first and secondtemporary values.

Preferably, the first temporary value may be a temporary value of theelement data obtained by the first data configuration process and thesecond temporary value may be a temporary value of the element dataobtained by the second data configuration process.

Accordingly, since the data configuration process needs to be repeatedlyperformed only twice, calculation is simplified.

Preferably, the data configuration process may include a first processof converting temporary values of the M pieces of element data intotemporary values of the N pieces of detection data based on the Npredetermined rates set to each of the M pieces of element data, asecond process of calculating N first coefficients indicatingmagnifications by which temporary values of the N pieces of detectiondata are to be multiplied so that the temporary values of the N piecesof detection data become equal to the N pieces of detection data, athird process of converting the N first coefficients into M secondcoefficients indicating magnifications by which the M pieces of elementdata are to be multiplied based on the N predetermined rates set to eachof the M pieces of element data, and a fourth process of correcting thetemporary values of the M pieces of element data based on the M secondcoefficients.

Preferably, in the first process, the element data configuration unitmay convert a matrix having temporary values of the M pieces of elementdata as components into a matrix having temporary values of the N piecesof detection data as components based on a first conversion matrixincluding M×N components corresponding to the M pieces of element dataand the N pieces of detection data, one component corresponding to thepredetermined rate associated with the single partial element datadistributed to the single detection data from the single element data.

Preferably, in the third process, the element data configuration unitmay convert a matrix having the N first coefficients as components intoa matrix having the M second coefficients as components based on asecond conversion matrix including M×N components corresponding to the Mpieces of element data and the N pieces of detection data, one componentcorresponding to the predetermined rate associated with the singlepartial element data distributed to the single detection data from thesingle element data.

Preferably, in the first data configuration process, the element dataconfiguration unit may omit the first process but perform the secondprocess using predetermined N initial values as temporary values of theN pieces of detection data.

Since the first process is omitted, a processing speed is improved.

Preferably, in the first data configuration process, the element dataconfiguration unit may perform the first process using M initial valuesbased on at least a group of M pieces of element data which has beenjust configured as temporary values of the M pieces of element data.

Since the first process is performed using initial values based on theelement data which has been just configured, accuracy of the configuredM pieces of element data is improved.

Preferably, the sensor unit may include N electrodes formed in therespectively different detection regions and an electrostaticcapacitance detection unit configured to generate detection datacorresponding to first electrostatic capacitances in portions betweenthe object approaching the operation plane and the electrodes for eachof the N electrodes. The single partial element data may be approximatedto a second electrostatic capacitance generated between an overlappingportion of the single electrode in the single section and the object.The single element data may be approximated to a third electrostaticcapacitance obtained by combining all the second electrostaticcapacitances in the single section.

In this case, each of the predetermined rates may have a valuecorresponding to a rate of an area of an overlapping portion of acorresponding one of the electrodes in a corresponding one of thesections to an area of overlapping portions of all the electrodes in thecorresponding one of the sections.

With this configuration, the element data corresponding to electrostaticcapacitances between an overlapping portion of at least one electrodeand the object are configured in each of the M sections on the operationplane.

Preferably, the sensor unit may include a plurality of electrodes whichare formed in the respectively different detection regions and whichhave N terminals as a whole, each of the electrodes having a pluralityof terminals, and an electrostatic capacitance detection unit configuredto receive charges accumulated in portions between an object approachingthe operation plane and the electrodes from the N terminals respectivelyand generate the detection data corresponding to electrostaticcapacitances between the object and the electrodes for each of the Nterminals based on the received charges. The electrostatic capacitancedetection unit may simultaneously input the charges accumulated in oneof the electrodes from the plurality of terminals disposed in theelectrode. By the simultaneous input, partial charges accumulated inportions between an overlapping portion of the single electrode in thesingle section and the object may be distributed to each of theplurality of terminals as distribution charges in accordance withconductance in a range from the overlapping portion to each of theplurality of terminals. The single partial element data may beapproximated to the distribution charge to be distributed to the singleterminal by the simultaneous input. The single element data may beapproximated to a combined charge obtained by combining all the partialcharges accumulated in the overlapping portions of all the electrodes inthe single section.

In this case, each of the predetermined rates may have a valuecorresponding to a rate of an area of an overlapping portion of acorresponding one of the electrodes in a corresponding one of thesections to an area of overlapping portions of all the electrodes in thecorresponding one of the sections and a rate of conductance in a rangefrom one of the terminals in the single electrode to the overlappingportion to conductance in a range from all the terminals in the singleelectrode to the overlapping portion.

With this configuration, the element data corresponding to theelectrostatic capacitances between at least one overlapping portion ofthe electrode and the object may be configured in each of the M sectionson the operation plane. Furthermore, since the plurality of terminalsare disposed on the single electrode and single detection data isgenerated for each terminal, the number of electrodes becomes smallerthan the number of detection data and a configuration of the sensor unitis simplified.

According to a second aspect of the present invention, there is providedan element data configuration method which causes an input deviceincluding a sensor unit which detects degrees of proximity of an objectin a plurality of different detection regions on an operation plane andgenerates N pieces of detection data in accordance with a result of thedetection to configure M pieces of element data indicating degrees ofproximity of the object in each of M sections (M is a natural numberlarger than N) which virtually divide the operation plane based on the Npieces of detection data. Each of the M sections has at least oneoverlapping portion which overlaps with the detection region. Each ofthe M pieces of element data is a sum of partial element datadistributed in predetermined rates to each of the N pieces of detectiondata, and each of the N pieces of detection data is approximated to asum of the partial element data distributed in the predetermined ratesfrom each of the M pieces of element data. The element dataconfiguration method includes: calculating respective temporary valuesof the N pieces of detection data as sums of the partial element datadistributed from each of temporary values of the M pieces of elementdata in the predetermined rates and repeatedly performs a dataconfiguration process of correcting the temporary values of the M piecesof element data at least twice based on the N predetermined rates setfor each of the M pieces of element data so that the calculatedtemporary values of the N pieces of detection data approximate the Npieces of detection data; calculating a coefficient having an absolutevalue which becomes smaller as a difference between the two temporaryvalues in each of the element data becomes larger based on the twotemporary values obtained by the data configuration process performedtwice for each of the M pieces of element data; and calculating, foreach of the M sections, a sum of a value obtained by multiplying adifference between a first temporary value of the element data obtainedby the first data configuration process and a second temporary value ofthe element data obtained by the second data configuration process bythe coefficient and the first temporary value as an estimation value ofthe element data obtained by repeatedly performing the dataconfiguration process.

According to a third aspect of the present invention, there is provideda program that causes a computer to execute the element dataconfiguration method according to the second aspect.

According to the present invention, element data indicating a degree ofproximity of an object in a plurality of sections on an operation planecan be configured by a simple calculation using a number of detectiondata smaller than the number of sections.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram illustrating an example of a configuration of aninput device according to a first embodiment;

FIGS. 2A to 2B are diagrams illustrating a plurality of sectionsobtained by virtually dividing an operation plane, where FIG. 2A is adiagram illustrating a plurality of sections and FIG. 2B is a diagramillustrating overlapping of a detection region on sections;

FIG. 3 is a diagram illustrating the relationship between N pieces ofdetection data and M pieces of partial element data;

FIG. 4 is a diagram explaining conversion from the M pieces of elementdata into the N pieces of detection data;

FIG. 5 is a diagram explaining conversion from temporary values of the Mpieces of element data into temporary values of the N pieces ofdetection data;

FIG. 6 is a diagram explaining conversion from N first coefficients intothe M second coefficients;

FIG. 7 is a flowchart of an example of a method for configuring M piecesof element data using N pieces of detection data in the input deviceaccording to the first embodiment;

FIG. 8 is a flowchart of an example of a data configuration process;

FIGS. 9A and 9B are diagrams illustrating an example of a simulationresult of the element data configuration process in a case where adistance of two objects is comparatively short which is repeatedlyperformed a large number of times, where FIG. 9A is a diagramillustrating a two-dimensional distribution of approach degrees ofobjects which are virtually set as a condition for the simulation andFIG. 9B is a diagram illustrating a two-dimensional distribution ofelement data which is converged after the data configuration process isrepeatedly performed 1000 times;

FIGS. 10A and 10B are diagrams illustrating an example of a simulationresult of the element data configuration process in the input deviceaccording to the first embodiment under the same condition as FIG. 9A,where FIG. 10A is a diagram illustrating the correlation between a valueobtained by subtracting a first temporary value from a second temporaryvalue and a value obtained by subtracting the first temporary value froma convergence value and FIG. 10B is a diagram illustrating atwo-dimensional distribution of element data estimated using acoefficient calculated using a result of the data configuration processperformed twice;

FIGS. 11A and 11B are diagrams illustrating an example of a simulationresult of the element data configuration process in a case where adistance of two objects is a middle degree which is repeatedly performeda large number of times, where FIG. 11A is a diagram illustrating atwo-dimensional distribution of approach degrees of the objects whichare virtually set as a condition for the simulation and FIG. 11B is adiagram illustrating a two-dimensional distribution of element datawhich is converged after the data configuration process is repeatedlyperformed 1000 times;

FIGS. 12A and 12B are diagrams illustrating an example of a simulationresult of the element data configuration process in the input deviceaccording to the first embodiment under the same condition as FIG. 11A,where FIG. 12A is a diagram illustrating the correlation between a valueobtained by subtracting a first temporary value from a second temporaryvalue and a value obtained by subtracting the first temporary value froma convergence value and FIG. 12B is a diagram illustrating atwo-dimensional distribution of element data estimated using acoefficient calculated using a result of the data configuration processperformed twice;

FIGS. 13A and 13B are diagrams illustrating an example of a simulationresult of the element data configuration process in a case where adistance of two objects is comparatively long which is repeatedlyperformed a large number of times, where FIG. 13A is a diagramillustrating a two-dimensional distribution of approach degrees of theobjects which are virtually set as a condition for the simulation andFIG. 13B is a diagram illustrating a two-dimensional distribution ofelement data which is converged after the data configuration process isrepeatedly performed 1000 times;

FIGS. 14A and 14B are diagrams illustrating an example of a simulationresult of the element data configuration process in the input deviceaccording to the first embodiment under the same condition as FIG. 13A,where FIG. 14A is a diagram illustrating the correlation between a valueobtained by subtracting a first temporary value from a second temporaryvalue and a value obtained by subtracting the first temporary value froma convergence value and FIG. 14B is a diagram illustrating atwo-dimensional distribution of element data estimated using acoefficient calculated using a result of the data configuration processperformed twice;

FIG. 15 is a diagram illustrating the correlation between an evaluationvalue D which is associated with a difference degree of two temporaryvalues obtained by performing the data configuration process twice and acoefficient γ;

FIGS. 16A and 16B are diagrams illustrating a simulation result obtainedwhen the element data configuration process is performed using acoefficient γ′ which is larger than the coefficient γ calculated basedon the evaluation value D under the same condition as FIG. 13A, whereFIG. 16A is a diagram illustrating the correlation between a valueobtained by subtracting a first temporary value from a second temporaryvalue and a value obtained by subtracting the first temporary value froma convergence value and FIG. 16B is a diagram illustrating atwo-dimensional distribution of element data estimated using thecoefficient γ′;

FIG. 17 is a flowchart of an example of a method for configuring Mpieces of element data using N pieces of detection data in an inputdevice according to a second embodiment;

FIG. 18 is a diagram illustrating the correlation between an evaluationvalue D which is associated with a difference degree of two temporaryvalues obtained by performing a data configuration process twice and acoefficient γ and illustrating determination of conversion from theevaluation value D to the coefficient γ using two types of linearfunction having different inclinations;

FIGS. 19A and 19B are diagrams illustrating an example of a simulationresult of the element data configuration process in the input deviceaccording to the second embodiment under the same condition as FIG. 9A,where FIG. 19A is a diagram illustrating the correlation between a valueobtained by subtracting a first temporary value from a second temporaryvalue and a value obtained by subtracting the first temporary value froma convergence value and FIG. 19B is a diagram illustrating atwo-dimensional distribution of element data estimated using acoefficient calculated using a result of the data configuration processperformed twice;

FIG. 20 is a diagram illustrating an example of a configuration of aninput device according to a third embodiment;

FIG. 21 is a diagram illustrating a second electrostatic capacitancebetween an overlapping portion of a single electrode in a single sectionand an object;

FIGS. 22A and 22B are diagrams illustrating an example of a pattern ofelectrodes in the input device according to the third embodiment, whereFIG. 22A is a diagram illustrating a plurality of sections on anoperation plane and FIG. 22B is a diagram illustrating a pattern ofelectrodes overlapping with the individual sections;

FIGS. 23A and 23B are diagrams illustrating the pattern of electrodes ofFIG. 22B in detail, where FIG. 23A is a diagram illustrating a patternof electrodes formed on an upper layer and FIG. 23B is a diagramillustrating a pattern of electrodes formed on a lower layer;

FIG. 24 is a diagram illustrating an example of a configuration of aninput device according to a fourth embodiment;

FIG. 25 is a diagram illustrating a state in which charge is accumulatedbetween an overlapping portion of a single electrode in a single sectionand an object;

FIG. 26 is a diagram illustrating a state in which charge accumulated ina single electrode in a single section is distributed to two terminals;

FIGS. 27A and 27B are diagrams illustrating examples of a pattern ofelectrodes in the input device according to the fourth embodiment, whereFIG. 27A is a diagram illustrating a plurality of sections in anoperation plane and FIG. 27B is a diagram illustrating a pattern ofelectrodes overlapping with the individual sections;

FIGS. 28A and 28B are diagrams illustrating the pattern of electrodes ofFIG. 27B in detail, where FIG. 28A is a diagram illustrating a patternof electrodes formed on an upper layer and FIG. 28B is a diagramillustrating a pattern of electrodes formed on a lower layer;

FIG. 29 is a flowchart of a modification of a process of configuring Mpieces of element data using N pieces of detection data; and

FIG. 30 is a flowchart of another modification of a process ofconfiguring M pieces of element data from N pieces of detection data.

DESCRIPTION OF THE PREFERRED EMBODIMENTS First Embodiment

FIG. 1 is a diagram illustrating an example of a configuration of aninput device according to a first embodiment of the present invention.

The input device illustrated in FIG. 1 includes a sensor unit 10, aprocessor 20, a storage unit 30, and an interface unit 40. The inputdevice according to this embodiment is used to input informationcorresponding to a proximity position in case that an object, such as afinger or a pen, approaches an operation plane in which a sensor isprovided. Note that the term “proximity” in this specification means “tobe closely located” and does not limit a contact state or a non-contactstate.

Sensor Unit 10

The sensor unit 10 detects a degree of proximity of an object (such as afinger or a pen) in at least one detection region R on an operationplane 11 and generates N pieces of detection data S₁ to S_(N) as awhole. The sensor unit 10 generates at least one piece of detection dataS_(i) for each detection region R. Note that “i” indicates an integer ina range from 1 to N. In a description below, the N pieces of detectiondata S₁ to S_(N) are referred to as “detection data S” withoutdistinguishing the detection data S1 to SN from one another whereappropriate.

For example, the sensor unit 10 detects an electrostatic capacitancebetween an electrode disposed in the detection region R and an object,and generates detection data S_(i) corresponding to a result of thedetection. The sensor unit 10 may detect a degree of proximity of theobject to the detection region R in accordance with a physical amount(such as a resistance change in accordance with a contact pressure)other than the electrostatic capacitance.

The operation plane 11 of the sensor unit 10 is virtually divided into aplurality of sections A as illustrated in FIG. 2A. In the example ofFIG. 2A, the operation plane 11 is divided into a plurality of sectionsA in a grid. Furthermore, each of the plurality of sections A has atleast one portion overlapping with a detection region R. In an exampleof FIG. 2B, a single section A overlaps with four detection regions R.Accordingly, the sensor unit 10 generates at least one piece ofdetection data S indicating a degree of proximity of the object for eachof the plurality of sections A. It is assumed that the number ofsections A is M which is larger than N (M>N) hereinafter. Furthermore,each of the sections A is referred to as a “section A_(j)” whereappropriate in a distinguishable manner. Note that “j” indicates aninteger in a range from 1 to M.

The input device of this embodiment configures M pieces of element dataP₁ to P_(M) indicating degrees of proximity of the object in each of theM sections A₁ to A_(M) based on the N pieces of detection data S₁ toS_(N). In a description below, the M pieces of element data P₁ to P_(M)are referred to as “element data P” without distinguishing the elementdata P₁ to P_(M) from one another where appropriate.

The certain relationship is established between the M pieces of elementdata P₁ to P_(M) and the N pieces of detection data S₁ to S_(N).Specifically, each of the M pieces of element data P₁ to P_(M) isrepresented by a sum of partial element data U distributed to each ofthe N pieces of detection data S₁ to S_(N) in predetermined rates.Assuming that the partial element data U distributed from the elementdata P_(j) to the detection data S_(i) is indicated by “U_(ij)”, theelement data P is represented by the following equation.

$\begin{matrix}{P_{j} = {\sum\limits_{i = 1}^{N}\; U_{ij}}} & (1)\end{matrix}$

Furthermore, each of the N pieces of detection data S₁ to S_(N) isapproximated to a sum of the partial element data U_(ij) distributedfrom each of the M pieces of element data P₁ to P_(M) in predeterminedrates. The detection data S_(i) is represented by the followingequation.

$\begin{matrix}{S_{i} = {\sum\limits_{j = 1}^{M}\; U_{ij}}} & (2)\end{matrix}$

FIG. 3 is a diagram illustrating the relationship between the N piecesof detection data S₁ to S_(N) and the M pieces of element data P₁ toP_(M) and represents the relationships of Expressions (1) and (2). As isapparent from in FIG. 3, the detection data S_(i) is approximated to avalue obtained by adding the partial element data U_(il) to U_(iM) toone another distributed from a corresponding one of the N pieces ofdetection data S₁ to S_(N). Therefore, if the partial element dataU_(il) to U_(iM) can be calculated from the element data P₁ to P_(M),the detection data S_(i) may be calculated in accordance with Expression(2).

In the input device according to this embodiment, it is assumed that arate of the partial element data U_(ij) distributed to single detectiondata S_(i) in single element data P_(j) is constant. Assuming that thepredetermined rate is “constant data K_(ij)”, the constant data K_(ij)is represented by the following equation.

$\begin{matrix}{K_{ij} = \frac{U_{ij}}{P_{j}}} & (3)\end{matrix}$

When the partial element data U_(ij) obtained by Expression (3) isassigned to Expression (2), the detection data S_(i) is represented bythe following equation.

$\begin{matrix}{S_{i} = {\sum\limits_{j = 1}^{M}\; {K_{ij}P_{j}}}} & (4)\end{matrix}$

FIG. 4 is a diagram illustrating conversion from the M pieces of elementdata P₁ to P_(M) into the N pieces of detection data S₁ to S_(N). Theconversion from the element data P₁ to P_(M) into the detection data S₁to S_(N) represented by Expression (4) is determined by N×M constantdata K_(ij). This conversion is represented by the following equationusing matrices as is apparent from FIG. 4.

$\begin{matrix}{{\underset{\underset{K}{}}{\begin{bmatrix}K_{11} & K_{12} & \ldots & K_{1M} \\K_{21} & \; & \; & K_{2M} \\\vdots & \; & \; & \vdots \\K_{N\; 1} & K_{N\; 2} & \ldots & K_{NM}\end{bmatrix}}\mspace{11mu}\begin{bmatrix}P_{1} \\P_{2} \\\vdots \\P_{M}\end{bmatrix}} = \begin{bmatrix}S_{1} \\S_{2} \\\vdots \\S_{N}\end{bmatrix}} & (5)\end{matrix}$

A matrix of N rows by M columns (a first conversion matrix K) on a leftmember of Expression (5) is general data defined by a configuration ofthe sensor unit 10, such as a state of overlapping between the detectionregions R and the sections A and detection sensitivity for detectingoverlapping portions of each of the detection regions R in each of thesections A of the sensor unit 10.

Processor 20

The processor 20 is a circuit which controls an entire operation of theinput device, and is constituted by including, for example, a computerwhich performs a process in accordance with an instruction code of aprogram 31 stored in the storage unit 30, and a logic circuit whichrealizes a specific function. All processes of the processor 20 may berealized in accordance with programs in the computer, or some of or allthe processes may be realized by a dedicated logic circuit.

In the example of FIG. 1, the processor 20 includes a controller 21, anelement data configuration unit 22, and a coordinate calculation unit23.

The controller 21 controls a timing of detection performed by the sensorunit 10. For example, the controller 21 controls various circuitsincluded in the sensor unit 10 such that selection of one of thedetection regions R to be subjected to detection, sampling of an analogsignal obtained as a result of the detection, generation of detectiondata S by means of A/D conversion, and the like are performed atappropriate timings.

The element data configuration unit 22 performs a process of configuringthe M pieces of element data P₁ to P_(M) corresponding to the M sectionsA based on the N pieces of detection data generated by the sensor unit10.

Although the element data configuration unit 22 is capable of convergingthe M pieces of element data P₁ to P_(M) into a certain value byrepeatedly performing a data configuration process described below alarge number of times, the data configuration process is executed twiceso that a calculation process is simplified. Then the element dataconfiguration unit 22 obtains the M pieces of element data P₁ to P_(M)(definite values) by a comparatively simple calculation process based ontemporary values PA₁ to PA_(M) of the M pieces of element data obtainedby each of the two data configuration processes. Hereinafter, in adescription below, the temporary values PA₁ to PA_(M) of the M pieces ofelement data are referred to as a “temporary value PA” withoutdistinguishing the temporary values PA₁ to PA_(M) from one another whereappropriate.

First, the data configuration process will be described. The elementdata configuration unit 22 calculates respective temporary values SA₁ toSA_(N) of the N pieces of detection data as sums of the partial elementdata U_(ij) distributed from each of the temporary values PA₁ to PA_(M)of the M pieces of element data in predetermined rates (constant dataK_(ij)) in the first data configuration process. Then the element dataconfiguration unit 22 corrects the temporary values PA₁ to PA_(M) of theM pieces of element data based on the N×M constant data K_(ij) so thatthe calculated temporary values SA₁ to SA_(N) of the N pieces ofdetection data become close to the N pieces of detection data S₁ toS_(N) which are results of the detection performed by the sensor unit10.

Specifically, the data configuration process includes four processes(first to fourth processes).

First Process

In the first process, the element data configuration unit 22 convertsthe temporary values PA₁ to PA_(M) of the M pieces of element data intothe temporary values SA₁ to SA_(N) of the N pieces of detection databased on the N×M constant data K_(ij) which have been obtained. Theconversion is represented by the following equation using the firstconversion matrix K in accordance with the relationship illustrated inExpression (5).

$\begin{matrix}{{\underset{\underset{K}{}}{\begin{bmatrix}K_{11} & K_{12} & \ldots & K_{1M} \\K_{21} & \; & \; & K_{2M} \\\vdots & \; & \; & \vdots \\K_{N\; 1} & K_{n\; 2} & \ldots & K_{NM}\end{bmatrix}}\mspace{11mu}\begin{bmatrix}{PA}_{1} \\{PA}_{2} \\\vdots \\{PA}_{M}\end{bmatrix}} = \begin{bmatrix}{SA}_{1} \\{SA}_{2} \\\vdots \\{SA}_{N}\end{bmatrix}} & (6)\end{matrix}$

FIG. 5 is a diagram explaining conversion from the temporary values PA₁to PA_(M) of the M pieces of element data into the temporary values SA₁to SA_(N) of the N pieces of detection data. As the first conversionmatrix K has been obtained in advance, when the temporary values PA₁ toPA_(M) of the M pieces of element data are given, the temporary valuesSA₁ to SA_(N) of the N pieces of detection data can be obtained inaccordance with Expression (6).

Second Process

In the second process, the element data configuration unit 22 calculatesN first coefficients α₁ to α_(N) indicating magnifications by which thetemporary values SA₁ to SA_(N) of the N pieces of detection data are tobe multiplied so that the temporary values SA₁ to SA_(N) become equal tothe N pieces of detection data S₁ to S_(N). The first coefficient α_(i)is represented by the following equation.

$\begin{matrix}{\alpha_{i} = \frac{S_{i}}{{SA}_{i}}} & (7)\end{matrix}$

The calculation of the first coefficients α₁ to α_(N) in the secondprocess is represented as follows using matrices.

$\begin{matrix}{\begin{bmatrix}\alpha_{1} \\\alpha_{2} \\\vdots \\\alpha_{N}\end{bmatrix} = \begin{bmatrix}{S_{1}\text{/}{SA}_{1}} \\{S_{2}\text{/}{SA}_{2}} \\\vdots \\{S_{n}\text{/}{SA}_{N}}\end{bmatrix}} & (8)\end{matrix}$

Third Process

In the third process, the element data configuration unit 22 calculatesM second coefficients β₁ to β_(M) indicating magnifications by which thetemporary values PA₁ to PA_(M) of the M pieces of element data are to bemultiplied. Specifically, the element data configuration unit 22converts the N first coefficients α₁ to α_(N) into the M secondcoefficients β₁ to β_(M) based on the N×M constant data K_(ij).

As illustrated by Expression (3), the partial element data U_(ij)distributed from the element data P_(j) to the element data S_(i) has arate corresponding to the constant data K_(ij) relative to the entireelement data P_(j). The larger the constant data K_(ij) is, the higherthe correlation between the element data P_(j) and the detection dataS_(i) is. Accordingly, it is estimated that the larger the constant dataK_(ij) is, the higher the correlation between the first coefficientα_(i) and the second coefficient β_(j) is. Therefore, the element dataconfiguration unit 22 does not merely average the N first coefficientsα₁ to α_(N) when the second coefficient β_(j) is calculated but averagesthe N first coefficients α₁ to α_(N) after weighting the N firstcoefficients α1 to αN by the constant data K_(ij). Specifically, thesecond coefficient β_(j) is represented by the following equation.

$\begin{matrix}{\beta_{j} = {\sum\limits_{i = 1}^{N}{K_{ij}\alpha_{i}}}} & (9)\end{matrix}$

FIG. 6 is a diagram explaining conversion from the N first coefficientsα₁ to α_(N) into the M second coefficients β₁ to β_(M). As illustratedin FIG. 6, the relationship of Expression (9) is represented by thefollowing equation using matrices.

$\begin{matrix}{{\underset{\underset{K^{T}}{}}{\begin{bmatrix}K_{11} & K_{21} & \cdots & K_{N\; 1} \\K_{12} & \; & \; & K_{N\; 2} \\\vdots & \; & \; & \vdots \\K_{1M} & K_{2M} & \cdots & K_{NM}\end{bmatrix}}\begin{bmatrix}\alpha_{1} \\\alpha_{2} \\\vdots \\\alpha_{N}\end{bmatrix}} = \begin{bmatrix}\beta_{1} \\\beta_{2} \\\vdots \\\beta_{M}\end{bmatrix}} & (10)\end{matrix}$

A matrix of M rows by N columns (a second conversion matrix K^(T)) on aleft side in Expression (10) is a transposed matrix of the firstconversion matrix K.

Fourth Process

In the fourth process, the element data configuration unit 22 correctsthe temporary values PA₁ to PA_(M) of the current element data so as toobtain new temporary values PA′₁ to PA′_(M) based on the M secondcoefficients β₁ to β_(M) obtained in the third process.

PA′ _(j)=β_(j) PA _(j)  (11)

Calculation to obtain the temporary values PA′₁ to PA′_(M) of theelement data in the fourth process is represented by the followingequation using matrices.

$\begin{matrix}{\begin{bmatrix}{PA}_{1}^{\prime} \\{PA}_{2}^{\prime} \\\vdots \\{PA}_{M}^{\prime}\end{bmatrix} = \begin{bmatrix}{\beta_{1}{PA}_{1}} \\{\beta_{2}{PA}_{2}} \\\vdots \\{\beta_{M}{PA}_{M}}\end{bmatrix}} & (12)\end{matrix}$

The element data configuration unit 22 repeatedly performs the dataconfiguration process described above at least twice. Then the elementdata configuration unit 22 calculates a definite value of the elementdata P_(j) based on a temporary value PA_(j) (a first temporary value)of the element data obtained by the proceeding data configurationprocess and a temporary value PA_(j) (a second temporary value) of theelement data obtained by the succeeding data configuration process.Specifically, the element data configuration unit 22 calculates a sum ofa value obtained by multiplying a difference between the first andsecond temporary values by the coefficient γ and the first temporaryvalue as the definite value of the element data P_(j). The definitevalue of the element data P_(j) is represented by the followingequation.

P _(j)=γ×(PA _(j) ^(t=2) −PA _(j) ^(t=1))+PA _(j) ^(t=1)  (13)

In Expression (13), “t” denotes repetition order of the dataconfiguration process. Furthermore, “PA_(j) ^(t=1)” indicates thetemporary value PA_(j) (the first temporary value) of the element dataobtained by the first data configuration process, and “PA_(j) ^(t=2)”indicates the temporary value PA_(j) (the second temporary value) of theelement data obtained by the second data configuration process.

As described hereinafter with reference to FIGS. 10A, 12A, and 14A, itis likely that a difference between a convergence value of the elementdata obtained by repetition of the data configuration process and thefirst temporary value is proportional to a difference between the secondtemporary value and the first temporary value. Accordingly, a sum of avalue obtained by multiplying the difference between the first andsecond temporary values by a proportionality coefficient γ and the firsttemporary value is approximated to the convergence value of the elementdata obtained by repetition of the data configuration process. Theelement data configuration unit 22 calculates a definite value of theelement data P_(j) in accordance with Expression (13) for each of the Msections A₁ to A_(M).

Note that, in a case where “q” and “r” are appropriate positive integersand q is smaller than r, “t=1” in Expression (13) may be replaced by“t=q”, and “t=2” may be replaced by “t=r”. In other words, the definitevalue of the element data P can be calculated based on the firsttemporary value PA_(j) ^(t=q) obtained by a q-th data configurationprocess and the second temporary value PA_(j) ^(t=r) obtained by an r-thdata configuration process performed after the q-th data configurationprocess.

Next, a method for calculating the coefficient γ used to obtain the Mpieces of element data P₁ to P_(M) (definite values) will be described.

As described hereinafter with reference to FIGS. 10A to 14B, when therelative positional relationship of an object approaching the operationplane 11 is changed, a difference (a difference degree) between the twotemporary values PA obtained by the data configuration process performedtwice on each of the M pieces of element data P is changed. Furthermore,it is likely that, as the difference (the difference degree) between thetwo temporary values PA in each of the element data P becomes large, anabsolute value of the coefficient γ becomes small. Therefore, theelement data configuration unit 22 calculates the coefficient γ so thatthe absolute value becomes small as the difference (the differencedegree) between the two temporary values PA in each of the element dataP becomes large.

For example, the element data configuration unit 22 calculates anevaluation value D corresponding to the difference degree of the twotemporary values PA in each of the M pieces of element data P, andobtains a value of a predetermined function using the evaluation value Das a variable as the coefficient γ.

The difference degree of the two temporary values PA is, for example, anabsolute value of a difference between the two temporary values PA. Theelement data configuration unit 22 calculates the evaluation value Daccording to a sum of the M difference degrees (absolute values ofdifferences between the two temporary values PA) corresponding to Mpieces of element data P.

As described hereinafter with reference to FIG. 15 and the like, whenthe sum of the M difference degrees (the absolute values of thedifferences between the two temporary values PA) corresponding to the Mpieces of element data P is determined as the evaluation value D, thecoefficient γ may be approximated by a linear function having a negativeinclination having the evaluation value D as a variable.

For example, the evaluation value D and the coefficient γ are calculatedby the following equations.

$\begin{matrix}{D = {\sum\limits_{j = 1}^{M}{{{PA}_{j}^{t = 2} - {PA}_{j}^{t = 1}}}}} & \left( {14\text{-}1} \right) \\{\gamma = {{a_{1} \times D} + b_{1}}} & \left( {14\text{-}2} \right)\end{matrix}$

The evaluation value D of Expression (14-1) is obtained by addingabsolute values (difference degrees) of differences between the firsttemporary values PA_(j) ^(t=1) of the element data obtained by the firstdata configuration process and the second temporary values PA_(j) ^(t=2)obtained in the second data configuration process. Furthermore, thecoefficient γ of Expression (14-2) is a linear function having aninclination of “a₁” and an intercept of “b₁”.

Note that the two temporary values PA of the element data P used for thecalculation of the evaluation value D may not be the same as the firstand second temporary values (Expression (13)) used for the calculationof the definite value of the element data P. For example, as anotherembodiment of the present invention, an absolute value of a differencebetween a temporary value PA_(j) ^(t=q) obtained by a q-th dataconfiguration process (q is an integer larger than 1) and a temporaryvalue PA_(j) ^(t=r) obtained by a r-th data configuration process (r isan integer larger than q) may be determined as the difference degree ofthe two temporary values PA corresponding to the element data P_(j).Also in this case, the evaluation value D may be calculated by adding Mdifference degrees corresponding to the M pieces of element data P toone another.

Furthermore, the difference degree of the two temporary values is notlimited to the absolute value of the difference between the twotemporary values. As another embodiment of the present invention, thedifference degree may be specified in accordance with a rate of the twotemporary values PA. For example, the difference degree may be specifiedby a rate of a larger one of the two temporary values PA which serves asa numerator to a smaller one of the two temporary values PA which servesas a denominator. Even the difference degree specified as describedabove becomes larger as the difference between the two temporary valuesPA becomes larger.

Furthermore, a function of the evaluation value D which approximates thecoefficient γ may be a function other than the linear function (aquadratic or higher-order polynomial function or the like). The functionof the evaluation value D which specifies the coefficient γ may bedetermined by, for example, a least-square method in accordance with aresult of simulation of the coefficient γ and the evaluation value and aresult of an actual measurement.

Furthermore, the function of specifying the conversion from theevaluation value D into the coefficient γ is not limited to thoserepresented by mathematical expressions. For example, the conversionfrom the evaluation value D into the coefficient γ may be specifiedbased on a data table showing the corresponding relation between theevaluation value D and the coefficient γ.

The element data configuration unit 22 has been described as above.

The coordinate calculation unit 23 calculates a coordinate of a portionon the operation plane 11 approached by an object (a finger, a pen orthe like) based on the element data P₁ to P_(M) configured by theelement data configuration unit 22. For example, the coordinatecalculation unit 23 binarizes two-dimensional data represented by theelement data P₁ to P_(M) and specifies a region of gathered dataindicating that the object has approached as an approach region of theobject. Then the coordinate calculation unit 23 generates profile datafor a horizontal direction and a vertical direction of the specifiedapproach region of the object. The profile data in the horizontaldirection is obtained by calculating a sum of the element data P_(j)serving as a group in the vertical direction of the operation plane 11for each column and arranging the sums of the element data P in thehorizontal direction of the operation plane 11. The profile data in thevertical direction is obtained by calculating a sum of the element dataP_(j) serving as a group in the horizontal direction of the operationplane 11 for each row and arranging the sums of the element data P inthe vertical direction of the operation plane 11. The coordinatecalculation unit 23 calculates a position of a peak of the element dataP_(j) and a position of the center of gravity of the element data P_(j)for the profile data in the horizontal direction and the profile data inthe vertical direction. The calculated position in the horizontaldirection and the calculated position in the vertical direction indicatea coordinate in which the object approaches the operation plane 11. Thecoordinate calculation unit 23 stores data on the coordinate obtained bythe calculation in a predetermined storage area of the storage unit 30.

Storage Unit 30

The storage unit 30 stores constant data and variable data to be used inprocesses performed by the processor 20. In case that the processor 20includes a computer, the storage unit 30 may store the program 31 to beexecuted by the computer. The storage unit 30 includes a volatilememory, such as a DRAM or an SRAM, a nonvolatile memory, such as a flashmemory, and a hard disk.

Interface Unit 40

The interface unit 40 is a circuit used for transmission and receptionof data between the input device and other control devices (such as anintegrated circuit (IC) for controlling an information device includingan input device). The processor 20 outputs information to be stored inthe storage unit 30 (such as information on a coordinate of an objectand the number of objects) from the interface unit 40 to a controldevice, not illustrated. Furthermore, the interface unit 40 may obtainthe program 31 executed by the computer included in the processor 20from a non-transitory recording medium, such as an optical disk or auniversal serial bus (USB) memory, or a server on a network and load theprogram 31 into the storage unit 30.

Here, a process of configuring the element data P performed by the inputdevice according to this embodiment will be described with reference toflowcharts of FIGS. 7 and 8.

ST100: The processor 20 obtains N pieces of detection data S₁ to S_(N)generated by the sensor unit 10.

ST105: The processor 20 obtains initial values of the temporary valuesPA₁ to PA_(M) of the element data to be used in the data configurationprocess (ST110) described below. The element data configuration unit 22obtains the constant data previously stored in the storage unit 30 as aninitial value, for example.

Note that the element data configuration unit 22 may obtain the elementdata P₁₁ to P_(M) obtained as a preceding configuration result (definitevalues) as initial values. Alternatively, the element data configurationunit 22 may, for example, calculate movement average values of theelement data based on a plurality of groups of element data P₁ to P_(M)which have been just obtained as a plurality of configuration results(definite values) and obtain the movement average values as initialvalues this time. When the first data configuration process (ST110) isperformed using the initial values based on at least one group of theelement data P₁ to P_(M) which have been just configured, accuracy ofthe configured element data is improved as compared with a case whereinitial values having a large error relative to the element data areused.

ST110: The processor 20 performs the data configuration process (FIG. 8)including the four processes (the first to fourth processes).

First, the processor 20 calculates temporary values SA₁ to SA_(N) of theN pieces of detection data in accordance with Expression (6) based onthe temporary values PA₁ to PA_(M) of the M pieces of element data andthe first conversion matrix K in the first process (ST200).

Next, the processor 20 calculates N first coefficients α₁ to α_(N) inaccordance with Expression (8) based on the temporary values SA₁ toSA_(N) of the N pieces of detection data and the N pieces of detectiondata S₁ to S_(NN) in the second process (ST205).

Thereafter, the processor 20 calculates M second coefficients β₁ toβ_(M) in accordance with Expression (10) based on the N firstcoefficients α₁ to α_(N) and the second conversion matrix K^(T) in thethird process (ST210). Subsequently, the processor 20 corrects theindividual temporary values PA₁₁ to PA_(M) of the M pieces of elementdata in accordance with Expression (12) using the second coefficients β₁to β_(M) in the fourth process (ST215).

The processor 20 calculates the M first temporary values PA₁ ^(t=1) toPA_(M) ^(t=1) by the data configuration process described above.

ST115: The processor 20 calculates the M second temporary values PA₁^(t=1) to PA_(M) ^(t=2) by performing the data configuration process(FIG. 8) which is the same as that described above on the M firsttemporary values PA₁ ^(t=1) to PA_(M) ^(t=1).

ST120: The processor 20 calculates an evaluation value D in accordancewith Expression (14-1) based on the M first temporary values PA₁ ^(t=1)to PA_(M) ^(t=1) and the M second temporary values PA₁ ^(t=2) to PA_(M)^(t=2).

ST125: The processor 20 calculates the coefficient γ in accordance withExpression (14-2) based on the evaluation value D calculated in stepST120.

ST145: The element data configuration unit 22 calculates a definitevalue of the element data P_(j) in accordance with Expression (13) basedon the first temporary value PA_(j) ^(t=1) and the second temporaryvalue PA_(j) ^(t=2) which are obtained by the data configuration processperformed twice (ST110 and ST115) and the proportionality coefficient γ.

Next, a result of simulation of configuration of the element data willbe described in detail with reference to FIGS. 9A to 14B. FIGS. 9A to14B are diagrams illustrating results of simulation performed for amethod for obtaining a convergence value of the element data P byrepeatedly performing the data configuration process (FIG. 8) a numberof times and for a method for obtaining an estimation value of theelement data P from results of the data configuration process performedtwice.

Here, simulation is performed for three cases which have differentrelative positional relationships between two objects (fingers or thelike) approaching the operation plane 11. FIGS. 9A and 9B and FIGS. 10Aand 10B are diagrams illustrating simulation results in a case where adistance between the two objects is comparatively short. FIGS. 11A and11B and FIGS. 12A and 12B are diagrams illustrating simulation resultsin a case where a distance between the two objects is aboutintermediate. FIGS. 13A and 13B and FIGS. 14A and 14B are diagramsillustrating simulation results in a case where a distance between thetwo object is comparatively long.

FIGS. 9A and 9B, FIGS. 11A and 11B, and FIGS. 13A and 13B showsimulation results in a case where a convergence value of the elementdata P is obtained by repeatedly performing the data configurationprocess a number of times. FIGS. 9A, 11A, and 13A are diagramsillustrating two-dimensional distributions of a proximity degree Px ofthe objects which is virtually set as a condition of the simulation. Inthe simulation, the sensor unit 10 calculates N pieces of detection dataS₁ to S_(N) based on the proximity degree Px, and element data P₁ toP_(M) are configured based on the detection data S₁ to S_(N). Anumerical value of the proximity degree Px is a dimensionless relativevalue. FIGS. 9B, 11B, and 13B are diagrams illustrating two-dimensionaldistributions of the element data Pc which is converged after the dataconfiguration process is repeatedly performed 1000 times. A numericalvalue of the element data Pc is also a dimensionless relative value.

Note that “X” and “Y” in the drawings of the two-dimensionaldistributions are coordinate axes indicating positions of the individualsections A and numbers on the coordinate axes are values of coordinates.

As is apparent from FIGS. 9B, 11B, and 13B, the two-dimensionaldistribution of the element data Pc which is converged by repeatedlyperforming the data configuration process many times is substantiallyapproximated to the two-dimensional distribution of the proximity degreePx of the object.

On the other hand, FIGS. 10A and 10B, FIGS. 12A and 12B, and FIGS. 14Aand 14B are diagrams illustrating simulation results of the element dataconfiguration process of this embodiment for obtaining an estimationvalue of the element data P based on the data configuration process(FIG. 8) performed twice. FIGS. 10A and 10B are diagrams illustratingsimulation results under a condition which is the same as the conditionof FIG. 9A (in the case where a distance between the two objects isshort). FIGS. 12A and 12B are diagrams illustrating simulation resultsunder a condition which is the same as the condition of FIG. 11A (in thecase where a distance between the two objects is about intermediate).FIGS. 14A and 14B are diagrams illustrating simulation results under acondition which is the same as the condition of FIG. 13A (in the casewhere a distance between the two objects is long).

FIGS. 10A, 12A, and 14A are diagrams illustrating the correlationbetween a value obtained by subtracting the first temporary value(PA_(j) ^(t=1)) from the second temporary value (PA_(j) ^(t=2)) and avalue obtained by subtracting the first temporary value (PA_(j) ^(t=1))from the convergence value (PA_(j) ^(t=L)). Axes of abscissae in eachdiagram denote a value obtained by subtracting the first temporary valuePA_(j) ^(t=1) obtained by the first data configuration process from thesecond temporary value PA_(j) ^(t=2) obtained by the second dataconfiguration process. Axes of ordinates in each diagram denote a valueobtained by subtracting the first temporary value PA_(j) ^(t=1) from thetemporary value PA_(j) ^(t=L) (the convergence value) obtained by theL-th (L=1000) data configuration process. Each of plots in FIGS. 10A,12A, and 14A corresponds to single element data P_(j).

As is apparent from FIGS. 10A, 12A, and 14A, the value obtained bysubtracting the first temporary value (PA_(j) ^(t=1)) from the secondtemporary value (PA_(j) ^(t=2)) and the value obtained by subtractingthe first temporary value (PA_(j) ^(t=1)) from the convergence value(PA_(j) ^(t=L)) have the proportional relationship. A coefficientrepresenting an inclination of the proportional relationship correspondsto the coefficient γ described above. Straight lines in each drawingindicate the coefficient γ calculated in accordance with Expressions(14-1) and (14-2). The straight lines substantially fit inclinations ofthe proportional relationship represented by distribution of the plots.

The inclinations of the proportional relationship indicated by thedistributions of the plots in FIGS. 10A, 12A, and 14A are changed inaccordance with the relative positional relationship of the two objectsapproaching the operation plane 11, and the longer a distance betweenthe objects becomes, the gentler the inclination becomes. Furthermore, adistribution range of values in the axes of abscissae (values obtainedby subtracting the first temporary values from the second temporaryvalues) is changed in accordance with the relative positionalrelationship between the two objects approaching the operation plane 11,and the longer the distance between the objects becomes, the larger anabsolute value of the value obtained by subtracting the first temporaryvalue from the second temporary value becomes as a whole. Accordingly,as results of the simulation, it is found that the larger an absolutevalue of a difference between the two temporary values in each of theelement data becomes, the gentler the inclinations of the proportionalrelationship indicated by the distributions of the plots in FIGS. 10A,12A, and 14A become.

FIGS. 10B, 12B, and 14B are diagrams illustrating a two-dimensionaldistribution of the element data P estimated by using the coefficient γcalculated in accordance with Expressions (14-1) and (14-2). As isapparent from a comparison between the simulation results of FIGS. 10B,12B, and 14B and the simulation results of FIGS. 9B, 11B, and 13B, atwo-dimensional distribution of the element data P estimated from aresult of the two data configuration processes is closely approximatedto a two-dimensional distribution of the element data Pc converged byrepetition of the data configuration process performed 1000 times.

FIG. 15 is a diagram illustrating the correlation between the evaluationvalue D calculated in accordance with Expression (14-1) and thecoefficient γ. The coefficient γ in an axis of ordinates in FIG. 15 isan optimum coefficient obtained by a numerical calculation based onsimulation results (FIGS. 10A, 12A, 14A, and the like) indicating thecorrelation between the value obtained by subtracting the firsttemporary value (PA_(j) ^(t=1)) from the second temporary value (PA_(j)^(t=2)) and the value obtained by subtracting the first temporary value(PA_(j) ^(t=1)) from the convergence value (PA_(j) ^(t=L)). Each ofplots in FIG. 15 corresponds to a single simulation result (FIG. 10A,12A, FIG. 14A, or the like). The different plots having differentevaluation values D may be obtained as illustrated in FIG. 15 byperforming simulation after changing the relative positionalrelationship of the plurality of objects approaching the operation plane11 in various manners.

As illustrated in FIG. 15, the coefficient γ indicating the proportionalrelationship between the value obtained by subtracting the firsttemporary value (PA_(j) ^(t=1)) from the second temporary value (PA_(j)^(t=2)) and the value obtained by subtracting the first temporary value(PA_(j) ^(t=1)) from the convergence value (PA_(j) ^(t=L)) tends to beapproximated to a linear function having a negative inclination and theevaluation value D as a variable. The inclination “a₁” in Expression(14-2) and the intercept “b₁” may be obtained by numerical calculation,such as a least-square method, using the simulation results of FIG. 15and a result of actual measurement.

FIGS. 16A and 16B are diagrams illustrating simulation result in a casewhere the element data configuration process is performed by using acoefficient γ′ which is larger than the coefficient γ calculated inaccordance with Expression (14-2) based on the evaluation value D. Thesimulation result is obtained under the condition of FIG. 13A (in thecase where a distance between the two objects is long). FIG. 16A is adiagram illustrating the correlation between the value obtained bysubtracting the first temporary value PA_(j) ^(t=1)) from the secondtemporary value (PA₁ ^(t=2)) and the value obtained by subtracting thefirst temporary value (PA_(j) ^(t=1)) from the convergence value (PA_(j)^(t=L)). FIG. 16B is a diagram illustrating a two-dimensionaldistribution of the element data P estimated by using the coefficient γ′in accordance with Expression (13).

As is apparent from a comparison between FIG. 16B and FIG. 14B, in acase where the coefficient γ′ which is shifted by an optimum value isused, the estimated two-dimensional distribution of the element data Phas a larger error relative to a two-dimensional distribution to bereproduced (FIG. 13A). In particular, in a region surrounded by a dottedline in FIG. 16B, the element data P has a negative value which issmaller than an actual value. Even if a weak peak indicating presence ofan object in a far position is included in the region, it is likely thatthe peak may be cancelled due to an error in a negative direction.Accordingly, the coefficient γ of an appropriate value calculated inaccordance with the relative positional relationship between the objectsapproaching the operation plane 11 is preferably used. By this, an errorof the element data described above is reduced.

As described above, according to this embodiment, each of the M sectionsA₁ to A_(M) which virtually divide the operation plane 11 has at leastone overlapping portion with the detection region R, and the sensor unit10 generates at least one piece of detection data S for each detectionregion R. Therefore, at least one piece of detection data S indicating adegree of proximity of an object is generated for each of the M sectionsA₁ to A_(M).

Furthermore, each of the M pieces of element data P₁ to P_(M) is a sumof partial element data U_(ij) distributed in predetermined rates (theconstant data K_(ij), Expression (3)) to the individual N pieces ofdetection data S₁ to S_(N) (Expression (1)), and each of the N pieces ofdetection data S₁ to S_(N) is approximated to the sum of the partialelement data U_(ij) distributed in the predetermined rates (the constantdata K_(ij)) from the individual M pieces of element data P₁ to P_(M)(Expression (2)). Specifically, conversion from the M pieces of elementdata P₁ to P_(M) to the N pieces of detection data S₁ to S_(N) isspecified (Expression (5)) by the N constant data K_(ij) set for theindividual M pieces of element data P₁ to P_(M) (Expression (5)).

In the data configuration process of the element data configuration unit22, the temporary values SA₁ to SA_(N) of the N pieces of detection dataare individually calculated as a sum of the partial element data U_(ij)distributed in the predetermined rates (the constant data K_(ij)) fromthe individual temporary value PA₁ to PA_(M) of the M pieces of elementdata (Expression (6)). Furthermore, the temporary values PA₁ to PA_(M)of the M pieces of element data are corrected based on the M×N constantdata K_(ij) so that the calculated temporary values SA₁ to SA_(N) of theN pieces of detection data become close to the N pieces of detectiondata S₁ to S_(N). By repeatedly performing the data configurationprocess many times, convergence values of the M pieces of element datasuitable for the N pieces of detection data S₁ to S_(N) may be obtained(FIGS. 9A and 9B, FIGS. 11A and 11B, and FIGS. 13A and 13B).

However, the element data configuration unit 22 repeatedly performs thedata configuration process at least twice so that a sum of a valueobtained by multiplying a difference between the first temporary value(PA_(j) ^(t=1)) of the element data obtained by the first dataconfiguration process and the second temporary value (PA_(j) ^(t=2)) ofthe element data obtained by the second data configuration process bythe coefficient γ and the first temporary value (PA_(j) ^(t=1)) iscalculated for each of the M sections A₁ to A_(M) as an estimation valueof the element data P obtained by repeatedly performing the dataconfiguration processes (Expression (13)). Accordingly, as compared withthe case where a convergence value of the element data P is obtained byrepeatedly performing the data configuration process many times, thenumber of repetition times for the data configuration process may beconsiderably reduced and calculation is simplified.

According to this embodiment, by calculating the estimation value of theelement data P by using the temporary value (PA_(j) ^(t=1)) of the firstdata configuration process and the temporary value (PA_(j) ^(t=2)) ofthe second data configuration process (Expression (13)), the dataconfiguration process is performed only twice and the calculation isconsiderably simplified.

Furthermore, the estimation value of the element data P obtained as asum of the value obtained by multiplying the difference between thefirst temporary value (PA_(j) ^(t=1)) and the second temporary value(PA_(j) ^(t=2)) by the coefficient γ and the first temporary value(PA_(j) ^(t=1)) has a certain degree of error relative to theconvergence value of the element data P obtained by repeatedlyperforming the data configuration process many times. An absolute valueof the coefficient γ which minimizes the error has a tendency to becomesmaller as the difference between the two temporary values PA becomeslarger in the element data P. Accordingly, the coefficient γ iscalculated such that the absolute value becomes small as the differencebetween the two temporary values PA becomes large in each of the Mpieces of element data P based on the two temporary values PA obtainedby the data configuration process performed twice on each of the Mpieces of element data P, so that an error from an optimum value of thecoefficient γ may be reduced as compared with a case where thecoefficient γ is set as a fixed value.

Furthermore, according to this embodiment, the evaluation value Dcorresponding to a difference degree of the two temporary values PA ineach of the M pieces of element data P is calculated, and a value of apredetermined function having the evaluation value D as a variable isobtained as the coefficient γ. In this way, an optimum coefficient γcorresponding to a difference degree of the two temporary values PA ineach of the M pieces of element data P may be obtained.

Furthermore, since the first temporary value (PA_(j) ^(t=1)) and thesecond temporary value (PA_(j) ^(t=2)) to be used in the calculation ofthe estimation value of the element data P (Expression (13)) are alsoused in calculation of the coefficient γ (Expression (14)), calculationof the coefficient γ may be easily performed.

Second Embodiment

Next, a second embodiment of the present invention will be described. Aninput device according to the second embodiment performs the process ofthe element data configuration unit 22 included in the input deviceaccording to the first embodiment except for a portion of the process,and other configurations of the input device are the same as those ofthe input device according to the first embodiment.

FIG. 17 is a flowchart of an example of a method for configuring Mpieces of element data from N pieces of detection data in the inputdevice according to the second embodiment. The flowchart of FIG. 17 isobtained by replacing step ST125 in the flowchart of FIG. 7 by stepST130, step ST135, and step ST140, and other steps are the same as thosein the flowchart of FIG. 7.

The element data configuration unit 22 selects a function to be used tocalculate a coefficient γ from among the following two equations inaccordance with the magnitude relationship between an evaluation value Dand a threshold value TH.

D>TH γ=α ₁ ×D+b ₁  (15-1)

D≤TH γ=α ₂ ×D+b ₂  (15-2)

When an evaluation value D calculated in step ST120 is larger than athreshold value TH (Yes in ST130), the element data configuration unit22 calculates the coefficient γ in accordance with Expression (15-1)(ST135), and when the evaluation value D is equal to or smaller than thethreshold value TH (No in ST130), the element data configuration unit 22calculates the coefficient γ in accordance with Expression (15-2)(ST140).

FIG. 18 is a diagram illustrating the correlation between the evaluationvalue D calculated in accordance with Expression (14-1) and thecoefficient γ. A graph illustrated in FIG. 18 is basically the same asthat of FIG. 15, but a range of the coefficient γ in an axis ofordinates is larger than that in FIG. 15.

As illustrated in FIG. 18, the element data configuration unit 22changes a linear function to be used to calculate the coefficient γ byusing a threshold value TH as a boundary. Specifically, when theevaluation value D is larger than the threshold value TH, the elementdata configuration unit 22 calculates the coefficient γ in accordancewith Expression (15-1) in which an absolute value of a negativeinclination is comparatively small, and when the evaluation value D isequal to or smaller than the threshold value TH, the element dataconfiguration unit 22 calculates the coefficient γ in accordance withExpression (15-2) in which an absolute value of a negative inclinationis comparatively large.

FIGS. 19A and 19B are diagrams illustrating an example of a simulationresult of the element data configuration process performed by the inputdevice according to this embodiment. The simulation result is obtainedunder the condition of FIG. 9A (in the case where a distance between twoobjects is short). FIG. 19A is a diagram illustrating the correlationbetween a value obtained by subtracting a first temporary value (PA_(j)^(t=1)) from a second temporary value (PA_(j) ^(t=t)) and a valueobtained by subtracting the first temporary value (PA_(j) ^(t=1)) from aconvergence value (PA_(j) ^(t=L)). FIG. 19B is a diagram illustrating atwo-dimensional distribution of the element data P estimated by usingthe coefficient γ obtained by a method of this embodiment.

As is apparent from a comparison between FIGS. 19B and 9B, a boundary (aposition of an arrow mark in FIG. 19B) between two objects in thetwo-dimensional distribution of FIG. 19B is clarified as compared withthe two-dimensional distribution of FIG. 9B. Accordingly, when adistance between the two objects is small (when the evaluation value Dis small), it is found that a boundary between the two objects isclarified by increasing an absolute value of an inclination of thelinear function to be used in the calculation of the coefficient γ.

As described hereinabove, according to this embodiment, as a distancebetween the objects approaching the operation plane 11 is reduced, adifference degree of the two temporary values PA for each of the Mpieces of element data P tends to be small, and accordingly, theevaluation value D also becomes small. Furthermore, when the distancebetween the objects is short, the boundary between the objectsapproaching the operation plane 11 tends to be clarified by increasing acoefficient γ (FIGS. 19A and 19B). Accordingly, by making an absolutevalue of an inclination (a₂) of the linear function in a range in whichthe evaluation value D is smaller than the threshold value TH to belarger than an absolute value of the inclination (a₁) of the linearfunction in a range in which the evaluation value D is larger than thethreshold value TH, the coefficient γ is easily increased when theevaluation value D is reduced since the distance between the objectsapproaching the operation plane 11 is reduced. By this, the boundarybetween the objects may be clarified as compared with the distributionof the element data P converted by the data configuration process whichis repeatedly performed.

Note that the function of calculating the coefficient γ by using theevaluation value D is not limited to the linear function but may be aquadratic function including a curved line. In this case, the sameeffect described above may be obtained when the coefficient γ iscalculated by using a function in which an absolute value of aderivative in a range in which the evaluation value D is smaller thanthe threshold value is larger than an absolute value of a derivative ina range in which the evaluation value D is larger than the thresholdvalue. Specifically, by making an absolute value of the derivative inthe range in which the evaluation value D is smaller than the thresholdvalue to be larger than an absolute value of the derivative in the rangein which the evaluation value D is larger than the threshold value, thecoefficient γ is easily increased when the evaluation value D is reducedsince the distance between the objects approaching the operation plane11 is reduced, and accordingly, it is possible to clarify the boundarybetween the objects.

Third Embodiment

Next, a third embodiment of the present invention will be described.FIG. 20 is a diagram illustrating an example of a configuration of aninput device according to the third embodiment. The input deviceaccording to this embodiment is obtained by embodying the sensor unit 10of the input device according to the first embodiment as a sensoremploying an electrostatic capacitance method, and an entireconfiguration is the same as the input device according to the firstembodiment.

A sensor unit 10A included in the input device of this embodiment has Nelectrodes E₁ to E_(N) formed in respective detection regions R. In adescription below, the N electrodes E₁ to E_(N) are referred to as an“electrode E” without distinguishing the N electrodes E₁ to E_(N) fromone another where appropriate.

Furthermore, the sensor unit 10A includes an electrostatic capacitancedetection unit 12 which generates detection data S corresponding to anelectrostatic capacitance (a first electrostatic capacitance) generatedbetween an object approaching an operation plane 11 and the electrode E.The electrostatic capacitance detection unit 12 generates the detectiondata S for each of the N electrodes E.

The electrostatic capacitance detection unit 12 samples chargescorresponding to electrostatic capacitances of capacitors formed betweenthe N detection electrodes and the object, and outputs detection data Scorresponding to the sampled charges. The electrostatic capacitancedetection unit 12 includes, for example, an electrostaticcapacitance/voltage conversion circuit (CV conversion circuit) and ananalog/digital (A/D) conversion circuit. Based on a control of theprocessor 20, the CV conversion circuit causes the capacitors formedbetween the N detection electrodes E and the object to be charged or toperform discharge, transfers charges of the capacitors transmittedthrough the detection electrodes E due to the charge/discharge tocapacitors for reference, and outputs signals corresponding to voltagesgenerated in the capacitors for reference. Based on a control of theprocessor 20, the A/D conversion circuit converts a signal output fromthe CV conversion circuit into a digital signal in a predetermined cycleso as to output detection data S. In a description hereinafter,detection data of an electrostatic capacitance of an electrode E_(i) isdenoted by “S_(i)”.

FIG. 21 is a diagram for explaining a second electrostatic capacitanceCE_(ij) between an overlapping portion E_(ij) of a single electrodeE_(i) in a single section A_(i) and an object 1. In FIG. 21, “E_(ij)”indicates an overlapping portion of the electrode E_(i) relative to thesection A_(j). Furthermore, “CE_(ij)” indicates an electrostaticcapacitance (a second electrostatic capacitance) formed between theoverlapping portion E_(ij) of the electrode E_(i) and the object 1, suchas a finger.

The number of electrodes E₁ to E_(N) is smaller than the number ofsections A₁ to A_(M), and the electrodes E₁ to E_(N) are disposed suchthat at least one electrode E has an overlapping portion E_(ij) in eachof the sections A.

Furthermore, the electrodes E₁ to E_(N) are disposed such that thedifferent electrodes E₁ to E_(N) have different combinations of thesections A for overlapping portions. For example, when the electrode E₁has overlapping portions in the sections A₁ and A₂, the other electrodesE have overlapping portions in the sections A other than the combinationof the sections A₁ and A₂. Note that, in a case where some of theelectrodes E have the overlapping portions in the same combination ofthe sections A, areas of the overlapping portions of the electrodes Emay be differentiated in at least portions of the sections.Specifically, the electrodes E₁ to E_(N) are disposed on the operationplane 11 so as to have different overlapping patterns on the sectionsA₁₁ to A_(M).

Assuming that an electrostatic capacitance generated between the entireoverlapping portion E_(ijij) of the electrode E included in the sectionA_(j) and the object 1 is referred to as a “third electrostaticcapacitance CA_(i)”, a change ΔCA_(i) of the third electrostaticcapacitance CA_(j) is substantially equal to a value obtained by addingsecond electrostatic capacitance changes ΔCE_(ij) of the electrodes E inthe section A_(j), and is represented by the following equation.

$\begin{matrix}{{\Delta \; {CA}_{j}} = {\sum\limits_{i = 1}^{N}{\Delta \; {CE}_{ij}}}} & (16)\end{matrix}$

In Expression (16), in case that the section A_(j) and the electrodeE_(i) do not have an overlapping portion E_(ij), the secondelectrostatic capacitance change ΔCE_(ij) is treated as zero.

When the electrostatic capacitance formed between the electrode E_(i)and the object is referred to as a “first electrostatic capacitanceCE_(i)”, a change ΔCE_(i) of the first electrostatic capacitance CE_(i)is substantially the same as a value obtained by adding of the changesΔCE_(ij) of the second electrostatic capacitances of all overlappingportions E_(ij) included in the electrode E_(i), and therefore, isrepresented by the following equation.

$\begin{matrix}{{\Delta \; {CE}_{i}} = {\sum\limits_{j = 1}^{M}{\Delta \; {CE}_{ij}}}} & (17)\end{matrix}$

The second electrostatic capacitance CE_(ij) formed between a singleoverlapping portion E_(ij) and the object 1 is substantiallyproportional to an area of the overlapping portion E_(ij). Furthermore,the third electrostatic capacitances CA_(j) (Expression (16)) formedbetween the overlapping portions of all the electrodes E_(i) included inthe section A_(j) and the object 1 are substantially proportional to anarea of all overlapping portions included in the section A_(j).Therefore, when a rate of an area of a single overlapping portion E_(ij)to an area of all overlapping portions which are positioned in the samesection A_(j) is represented as constant data K_(ij), as represented bythe following equation, the constant data K_(ij) represents a rate ofthe second electrostatic capacitance change ΔCE_(ij) to the thirdelectrostatic capacitance change ΔCA_(j).

$\begin{matrix}{K_{ij} = \frac{\Delta \; {CE}_{ij}}{\Delta \; {CA}_{j}}} & (18)\end{matrix}$

When the relationship of Expression (18) is used, Expression (17) isrepresented as follows.

$\begin{matrix}{{\Delta \; {CE}_{i}} = {\sum\limits_{j = 1}^{M}{K_{ij}\Delta \; {CA}_{j}}}} & (19)\end{matrix}$

Expression (19) is represented as follows using matrices.

$\begin{matrix}{{\underset{\underset{K}{}}{\begin{bmatrix}K_{11} & K_{12} & \cdots & K_{\; {1M}} \\K_{21} & \; & \; & K_{2M} \\\vdots & \; & \; & \vdots \\K_{N\; 1} & K_{N\; 2} & \cdots & K_{NM}\end{bmatrix}}\begin{bmatrix}{\Delta \; {CA}_{1}} \\{\Delta \; {CA}_{2}} \\\vdots \\{\Delta \; {CA}_{M}}\end{bmatrix}} = \begin{bmatrix}{\Delta \; {CE}_{1}} \\{\Delta \; {CE}_{2}} \\\vdots \\{\Delta \; {CE}_{N}}\end{bmatrix}} & (20)\end{matrix}$

Here, the element data P_(j) of the section A_(j) is proportional to thethird electrostatic capacitance change ΔCA_(j), the detection data S_(i)of the electrostatic capacitance detected by the electrostaticcapacitance detection unit 12 is proportional to the first electrostaticcapacitance change ΔCE_(i), and the partial element data U_(ij) of theoverlapping portion E_(ij) is proportional to the second electrostaticcapacitance change ΔCE_(ij). Specifically, the following expressions areestablished.

P _(j) ∝ΔCA _(j)  (21-1)

S _(i) ∝ΔCE _(i)  (21-2)

U _(ij) ∝ΔCE _(ij)  (21-3)

According to Expressions (21-1) to (21-3), Expressions (16) to (20) areequal to Expressions (1) to (5), respectively, described above.Accordingly, even in this embodiment, M pieces of element data P₁ toP_(M) may be configured by using N pieces of detection data S₁ to S_(N)similarly to the first embodiment.

FIGS. 22A and 22B are diagrams illustrating an example of an electrodepattern of the input device according to the third embodiment. In FIG.22A, 20 sections (A₁ to A₂₀) on the operation plane 11 are illustrated,and in FIG. 22B, 18 electrode patterns (E₁ to E₁₈) which overlap withthe individual sections A are illustrated. FIGS. 23A and 23B arediagrams illustrating the electrode patterns (E₁ to E₁₈) of FIG. 22B indetail. In FIG. 23A, eight electrode patterns (E₁ to E₈) formed on anupper layer are illustrated, and in FIG. 23B, ten electrode patterns (E₉to E₁₈) formed on a lower layer are illustrated.

In the examples of FIGS. 22A and 22B, the operation plane 11 of thesensor unit 10A has a substantially rectangle shape and is divided intoa grid pattern in a matrix of 4 rows by 5 columns by using the 20sections A₁ to A₂₀. The sections A₁ to A₅ are arranged starting from afirst row in a first column to the first row in a fifth column innumerical order, the sections A₆ to A₁₀ are arranged starting from asecond row in the first column to the second row in the fifth column innumerical order, the sections A₁₁ to A₁₅ are arranged starting from athird row in the first column to the third row in the fifth column innumerical order, and the sections A₁₆ to A₂₀ are arranged starting froma fourth row in the first column to the fourth row in the fifth columnin numerical order.

In the example of FIG. 23A, the electrodes E₁ to E₄ are positioned inthe first to fourth rows in the grid pattern in this order and extendfrom the first column to the fourth column. Rates of areas which areoccupied by the electrodes E₁ to E₄ in the individual sections are 4/8in the first column, 3/8 in the second column, 2/8 in the third column,and 1/8 in the fourth column. Furthermore, the electrodes E₅ to E₈ arepositioned in the first to fourth rows in the grid pattern in this orderand extend from the fifth column to the second column. Rates of areaswhich are occupied by the electrodes E₅ to E₈ in the individual sectionsare 4/8 in the fifth column, 3/8 in the fourth column, 2/8 in the thirdcolumn, and 1/8 in the second column.

In the example of FIG. 23B, the electrodes E₉ to E₁₃ are positioned inthe first to fifth columns in the grid pattern in this order and extendfrom the first row to the third row. Rates of areas which are occupiedby the electrodes E₉ to E₁₃ in the individual sections are 3/6 in thefirst row, 2/6 in the second row, and 1/6 in the third row. Furthermore,the electrodes E₁₄ to E₁₈ are positioned in the first to fifth columnsin the grid pattern in this order and extend from the fourth row to thesecond row. Rates of areas which are occupied by the electrodes E₁₄ toE₁₈ in the individual sections are 3/6 in the fourth row, 2/6 in thethird row, and 1/6 in the second row.

When the electrode E₁ in the first row is focused, the electrode E₁ hasan area of 4/8 of the section A₁₁, an area of 3/8 of the section A₂, anarea of 2/8 of the section A₃, and an area of 1/8 of the section A₄.Therefore, constant data K₁₁ of the electrode E₁ relative to the sectionA₁ is 4/8, constant data K₁₂ of the electrode E₁ relative to the sectionA₂ is 3/8, constant data K₁₃ of the electrode E₁ relative to the sectionA₃ is 2/8, and constant data K₁₄ of the electrode E₁ relative to thesection A₄ is 1/8. By performing the similar calculation, the firstconversion matrix K formed by constant data K_(ij) in a matrix of 18rows by 20 columns is represented as follows.

$\begin{matrix}\underset{\underset{K}{}}{\begin{bmatrix}0.5 & 0.38 & 0.25 & 0.13 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\0 & 0 & 0 & 0 & 0 & 0.5 & 0.38 & 0.25 & 0.13 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0.5 & 0.38 & 0.25 & 0.13 & 0 & 0 & 0 & 0 & 0 & 0 \\0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0.5 & 0.38 & 0.25 & 0.13 & 0 \\0 & 0.13 & 0.25 & 0.38 & 0.5 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\0 & 0 & 0 & 0 & 0 & 0 & 0.13 & 0.25 & 0.38 & 0.5 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0.13 & 0.25 & 0.38 & 0.5 & 0 & 0 & 0 & 0 & 0 \\0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0.13 & 0.25 & 0.38 & 0.5 \\0.5 & 0 & 0 & 0 & 0 & 0.33 & 0 & 0 & 0 & 0 & 0.17 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\0 & 0.5 & 0 & 0 & 0 & 0 & 0.33 & 0 & 0 & 0 & 0 & 0.17 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\0 & 0 & 0.5 & 0 & 0 & 0 & 0 & 0.33 & 0 & 0 & 0 & 0 & 0.17 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\0 & 0 & 0 & 0.5 & 0 & 0 & 0 & 0 & 0.33 & 0 & 0 & 0 & 0 & 0.17 & 0 & 0 & 0 & 0 & 0 & 0 \\0 & 0 & 0 & 0 & 0.5 & 0 & 0 & 0 & 0 & 0.33 & 0 & 0 & 0 & 0 & 0.17 & 0 & 0 & 0 & 0 & 0 \\0 & 0 & 0 & 0 & 0 & 0.17 & 0 & 0 & 0 & 0 & 0.33 & 0 & 0 & 0 & 0 & 0.5 & 0 & 0 & 0 & 0 \\0 & 0 & 0 & 0 & 0 & 0 & 0.17 & 0 & 0 & 0 & 0 & 0.33 & 0 & 0 & 0 & 0 & 0.5 & 0 & 0 & 0 \\0 & 0 & 0 & 0 & 0 & 0 & 0 & 0.17 & 0 & 0 & 0 & 0 & 0.33 & 0 & 0 & 0 & 0 & 0.5 & 0 & 0 \\0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0.17 & 0 & 0 & 0 & 0 & 0.33 & 0 & 0 & 0 & 0 & 0.5 & 0 \\0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0.17 & 0 & 0 & 0 & 0 & 0.33 & 0 & 0 & 0 & 0 & 0.5\end{bmatrix}} & (22)\end{matrix}$

As described above, even the input device according to the thirdembodiment which detects a degree of proximity of the object based on anelectrostatic capacitance may configure a larger number of element dataP than a number of detection data S by the calculation processsimplified similarly to the first embodiment.

Fourth Embodiment

Next, a fourth embodiment of the present invention will be described.FIG. 24 is a diagram illustrating an example of a configuration of aninput device according to a fourth embodiment. The input deviceaccording to this embodiment is obtained by replacing the sensor unit10A included in the input device according to the third embodiment by asensor unit 10B, and an entire configuration is the same as the inputdevice according to the third embodiment.

The sensor unit 10B has J electrodes ER₁ to ER_(J) formed in respectivedifferent detection regions R. In a description below, the J electrodesER₁ to ER_(J) are referred to as an “electrode ER” withoutdistinguishing the J electrodes ER₁ to ER_(J) from one another whereappropriate.

Each of the electrodes ER has a plurality of terminals T, and the Jelectrodes ER have N terminals T as a whole. In the example of FIG. 24,each of the electrodes ER has two terminals T, and therefore, the numberJ of the electrodes ER is half of the number N of terminals T. Notethat, as a modification of this embodiment, the electrode ER may have 3or more terminals T.

The electrode ER is formed of material having a resistance value higherthan those of general metal members (for example, ITO used for atransparent conductive film).

The electrostatic capacitance detection unit 12 inputs charges to beaccumulated between the object approaching the operation plane 11 andthe electrodes ER from the N terminals T, and generates detection data Scorresponding to electrostatic capacitances between the object and theelectrodes ER based on the input charges for each of the N terminals T.

Furthermore, when inputting a charge to be accumulated in a singleelectrode ER, the electrostatic capacitance detection unit 12simultaneously inputs the charge from the plurality of terminals Tdisposed in the single electrode ER. By this, the charge accumulated inthe electrode ER is distributed to the plurality of terminals T. Here,it is expected that a rate of the distribution of the charge isproportional to conductance (an inverse number of a resistance value) ina range from a portion in the electrode ER where the charge isaccumulated to the terminals T. Specifically, a larger amount of chargeis distributed to a terminal T having larger conductance.

FIG. 25 is a diagram illustrating a state in which a partial chargeQP_(kj) is accumulated between an overlapping portion ER_(kj) of asingle electrode ER_(k) in a single section A_(j) and the object 1. FIG.26 is a diagram illustrating a state in which the partial charge Q_(kj)is distributed to two terminals T_(k(1)) and T_(k(2)) of the electrodeER_(k). Note that “k” indicates an integer in a range from 1 to J.Furthermore, “k(1)” and “k(2)” indicate integers in a range from 1 to Nindividually associated with the integer k.

In FIGS. 25 and 26, “G_(k(1)j)” indicates conductance in a range fromthe overlapping portion ER_(kj) to the terminal T_(k(1)), and“G_(k(2)j)” indicates conductance in a range from the overlappingportion ER_(kj) to the terminal T_(k(2)). Furthermore, “CER_(kj)”indicates an electrostatic capacitance between the overlapping portionER_(kj) and the object 1.

In FIG. 26, “QD_(k(1)j)” indicates distribution charge distributed tothe terminal T_(k(1)) in the partial charge QP_(kj). Furthermore,“QD_(k(2)j)” indicates distribution charge distributed to the terminalT_(k(2)) in the partial charge QP_(kj).

The electrostatic capacitance detection unit 12 includes two chargeamplifiers 12-k(1) and 12-k(2) which simultaneously input charge fromthe two terminals T_(k(1)) and T_(k(2)). Each of the charge amplifiers12-k(1) and 12-k(2) includes an operation amplifier OP, a capacitor Cf,and switches SW1 and SW2. The capacitor Cf and the switch SW1 areconnected in parallel between an output of the operation amplifier OPand an inversion input terminal. The switch SW2 selectively inputs aground potential or a driving voltage V to a non-inversion inputterminal of the operation amplifier OP. The inversion input terminal ofthe operation amplifier OP is connected to a corresponding one of theterminals T of the electrode ER_(kj).

In the state of FIG. 25, the switches SW1 of the charge amplifiers12-k(1) and 12-k(2) are individually turned on, and the switches SW2individually input driving voltages V to the non-inversion inputterminals of the operation amplifiers OP. By this, a voltage which issubstantially the same as the driving voltage V is applied to the twoterminals T_(k(1)) and T_(k(2)), and the partial charge QP_(kj) isaccumulated between the overlapping portion ER_(kj) and the object 1.

In the state of FIG. 26, the switches SW1 of the charge amplifiers12-k(1) and 12-k(2) are simultaneously turned off, and the switches SW2simultaneously input the ground potential to the non-inversion inputterminals of the operation amplifiers OP. By this, charge is transferredto the charge amplifiers 12-k(1) and 12-k(2) so that the two terminalsT_(k(1)) and T_(k(2)) have the ground potential. The transfers of thecharge are almost simultaneously started.

The partial charge QP_(kj) is a sum of an distribution charge QD_(k(1)j)distributed to the terminal T_(k(1)) and an distribution chargeQD_(k(2)j) distributed to the terminal T_(k(2)), and the followingequation is established.

QP _(kj) =QD _(k(1)j) +QD _(k(2)j)  (23)

The distribution charge QD_(k(1)j) and QD_(k(2)j) are proportional toconductance G_(k(1)j) and G_(k(2)j) in the ranges from the overlappingportion ER_(kj) to the two terminals T_(k(1)) and T_(k(2)),respectively. Assuming that coefficients indicating conductance ratesare denoted by “KG_(k(1)j)” and “KG_(k(2)j)”, the distribution chargesQD_(k(1)j) and QD_(k(2)j) are represented by the following equations.

QD _(k(1)j) =KG _(k(1)j) ×QP _(kj)  (24-1)

QD _(k(2)j) =KG _(k(2)j) ×QP _(kj)  (24-2)

The coefficients KG_(k(1)j) and KG_(k(2)j) are represented by thefollowing equation using the conductance G_(k(1)j) and G_(k(2)j).

$\begin{matrix}{{KG}_{{k{(1)}}j} = \frac{G_{{k{(1)}}j}}{\left( {G_{{k{(1)}}j} + G_{{k{(2)}}j}} \right)}} & \left( {25\text{-}1} \right) \\{{KG}_{{k{(2)}}j} = \frac{G_{{k{(2)}}j}}{\left( {G_{{k{(2)}}j} + G_{{k{(2)}}j}} \right)}} & \left( {25\text{-}2} \right)\end{matrix}$

Furthermore, a combined charge obtained by combining all partial chargesQP_(kj) accumulated in the overlapping portions ER_(kj) of all theelectrodes ER_(k) in the section A_(j) is denoted by “Q_(j)”. Thecombined charge Q_(j) is represented as follows.

$\begin{matrix}{Q_{j} = {\sum\limits_{k = 1}^{J}{QP}_{kj}}} & (26)\end{matrix}$

The partial charge QP_(kj) is proportional to the electrostaticcapacitance CER_(kj) between the overlapping portion ER_(kj) and theobject 1 in the section A_(j), and the electrostatic capacitanceCER_(kj) is substantially proportional to an area of the overlappingportion ER_(kj). Accordingly, assuming that an area rate of theoverlapping portion ER_(kj) of the electrode ER_(k) in the section A_(j)to the overlapping portions of all the electrodes is denoted by“KS_(kj)”, the partial charge QP_(kj) is represented by the followingequation.

QP _(kj) =KS _(kj) ×Q _(j)  (27)

When Expression (27) is substituted for Expressions (24-1) and (24-2),the following equations are obtained.

QD _(k(1)j) =KG _(k(1)j) ×KS _(kj) ×Q _(j)  (28-1)

QD _(k(2)j) =KG _(k(2)j) ×KS _(kj) ×Q _(j)  (28-2)

In Expressions (28-1) and (28-2), when coefficients by which thecombined charge Q_(j) is multiplied are replaced by “K_(k(1)j)” and“K_(k(2)j)”, the coefficients are represented by the followingequations, respectively.

K _(k(1)j) =KG _(k(1)j) ×KS _(kj)  (29-1)

K _(k(2)j) =KG _(k(2)j) ×KS _(kj)  (29-2)

Since “k(1)” and “k(2)” are integers in a range from 1 to N, when “k(1)”and “k(2)” are replaced by an integer i, Expressions (29-1) and (29-2)are represented by the following equation.

K _(ij) =KG _(ij) ×KS _(kj)  (30)

When Expression (30) is substituted for Expressions (28-1) and (28-2),the distribution charge QD_(ij) is represented by the followingequation.

QD _(ij) =K _(ij) ×Q _(j)  (31)

When a detection charge input from a terminal T_(i) to the electrostaticcapacitance detection unit 12 is denoted by “QD_(i)”, the detectioncharge QD_(i) is obtained by adding all distribution charges QD_(ij)associated with the terminal T_(i) to one another, and therefore, thefollowing equation is obtained in accordance with Expression (31).

$\begin{matrix}{{QD}_{i} = {\sum\limits_{j = 1}^{M}{K_{ij}Q_{j}}}} & (32)\end{matrix}$

Expression (32) may be represented as follows by using matrices.

$\begin{matrix}{{\underset{\underset{K}{}}{\begin{bmatrix}K_{11} & K_{12} & \cdots & K_{\; {1M}} \\K_{21} & \; & \; & K_{2M} \\\vdots & \; & \; & \vdots \\K_{N\; 1} & K_{N\; 2} & \cdots & K_{NM}\end{bmatrix}}\begin{bmatrix}Q_{1} \\Q_{2} \\\vdots \\Q_{M}\end{bmatrix}} = \begin{bmatrix}{QD}_{1} \\{QD}_{2} \\\vdots \\{QD}_{N}\end{bmatrix}} & (33)\end{matrix}$

Furthermore, the combined charge Q_(j) in the section A_(j) is alsoobtained by adding all the distribution charges QD_(ij) associated withthe section A_(j), and is represented by the following equation.

$\begin{matrix}{Q_{j} = {\sum\limits_{i = 1}^{N}{QD}_{ij}}} & (34)\end{matrix}$

Here, the element data P_(j) of the section A_(j) is proportional to thecombined change Q_(j), the detection data S_(i) of the terminal T_(i)detected by the electrostatic capacitance detection unit 12 isproportional to the detection charge QD_(i), and the partial elementdata U_(ij) of the overlapping portion E_(ij) is proportional to thedistribution charge QD_(ij). Specifically, the following expressions areestablished.

P _(j) ∝Q _(j)  (35-1)

S _(i) ∝QD _(i)  (35-2)

U _(ij) ∝QD _(ij)  (35-3)

According to Expressions (35-1) to (35-3), Expressions (31), (32), (33),and (34) are equal to Expressions (3), (4), (5), and (1) describedabove, respectively. Accordingly, even in this embodiment, M pieces ofelement data P₁ to P_(M) may be configured by using N pieces ofdetection data S₁ to S_(N) similarly to the first embodiment.

FIGS. 27A and 27B are diagrams illustrating an example of electrodepatterns of the input device according to the fourth embodiment. In FIG.27A, 20 sections (A₁ to A₂₀) on the operation plane 11 are illustrated,and in FIG. 27B, 9 electrode patterns (ER₁ to ER₉) which overlap withthe individual sections A are illustrated. FIGS. 28A and 28B arediagrams illustrating the electrode patterns (ER₁ to ER₉) of FIG. 27B indetail. FIG. 28A shows four electrode patterns (ER₁ to ER₄) formed on anupper layer, and FIG. 28B shows five electrode patterns ER₅ to ER₉)formed on a lower layer.

The 20 sections A₁ to A₂₀ of FIG. 27A are arranged in a grid pattern ina matrix of 4 rows by 5 columns similarly to FIG. 22A.

In the example of FIG. 28A, the electrodes ER₁ to ER₄ are positioned infirst to fourth rows in the grid pattern in this order and individuallyextend from a first column to a fifth column. Rates of areas of theelectrodes ER₁ to ER₄ in each of the sections are all 1/2. Theelectrodes ER₁ to ER₄ have terminals T₁ to T₄, respectively, at its endportions on the first column side, and have terminals T₅ to T₈,respectively, at its end portions on the fifth column side.

In the example of FIG. 28B, the electrodes ER₅ to ER₉ are positioned inthe first to fifth columns in the grid pattern in this order and extendfrom the first row to the fourth row. Rates of areas of the electrodesER₅ to ER₉ in each of the sections are all 1/2. The electrodes ER₅ toER₉ have terminals T₉ to T₁₃, respectively, at its end portions on thefirst column side, and have terminals T₁₄ to T₁₈, respectively, at itsend portions on the fourth column side.

As an example, the terminal T₁ of the electrode ER₁ is focused. Theterminal T₁ is directly connected to an overlapping portion ER₁₁ of thesection A₁ and the electrode ER₁. Therefore, all the partial charge QP₁₁accumulated in the overlapping portion ER₁₁ is approximated to bedistributed to the terminal T₁. Furthermore, the partial charge QP₁₁ ishalf of a combined charge Q₁ in accordance with a rate of an area of theoverlapping portion ER₁₁ in the section A₁. Accordingly, constant dataK₁₁ of the electrode ER₁ relative to the section A₁ is 1/2.

An overlapping portion ER₁₂ in which the section A₂ and the electrodeER₁ are overlapped with each other is connected to the terminal T₁ withone section interposed therebetween and connected to the terminal T₅with three sections interposed therebetween. Therefore, in a partialcharge QP₁₂ accumulated in the overlapping portion ER₁₂, 3/4 of thepartial charge QP₁₂ is approximated to be distributed to the terminal T₁and 1/4 of the partial charge QP₁₂ is approximated to be distributed tothe terminal T₅. Furthermore, the partial charge QP₁₂ is half of acombined charge Q₂ in accordance with a rate of an area of theoverlapping portion ER₁₂ in the section A₂. Accordingly, constant dataK₁₂ of the electrode ER₁ relative to the section A₂ is 3/8.

An overlapping portion ER₁₃ in which the section A₃ and the electrodeER₁ overlap with each other is connected to the terminal T₁ with twosections interposed therebetween and connected to the terminal T₅ withtwo sections interposed therebetween. Therefore, in the partial chargeQP₁₃ accumulated in the overlapping portion ER₁₃, 1/2 of the partialcharge QP₁₃ is approximated to be distributed to the terminal T₁ and 1/2of the partial charge QP₁₃ is approximated to be distributed to theterminal T₅. Furthermore, the partial charge QP₁₃ is half of a combinedcharge Q₃ in accordance with a rate of an area of the overlappingportion ER₁₃ in the section A₃. Accordingly, constant data K₁₃ of theelectrode ER₁ relative to the section A₂ is 1/4.

An overlapping portion ER₁₄ in which the section A₄ and the electrodeER₁ overlap with each other is connected to the terminal T₁ with threesections interposed therebetween and connected to the terminal T₅ withone section interposed therebetween. Therefore, in the partial chargeQP₁₄ accumulated in the overlapping portion ER₁₄, 1/4 of the partialcharge QP₁₄ is approximated to be distributed to the terminal T₁ and 3/4of the partial charge QP₁₄ is approximated to be distributed to theterminal T₅. Furthermore, the partial charge QP₁₄ is half of a combinedcharge Q₄ in accordance with a rate of an area of the overlappingportion ER₁₄ in the section A₄. Accordingly, constant data K₁₄ of theelectrode ER₁ relative to the section A₄ is 1/8.

The terminal T₅ is directly connected to an overlapping portion ER₁₅ inwhich the section A₅ and the electrode ER₁ overlap with each other.Therefore, all the partial charge QP₁₅ accumulated in the overlappingportion ER₁₅ is approximated to be distributed to the terminal T₅.Accordingly, constant data K₁₅ of the electrode ER₁ relative to thesection A₅ is zero.

Accordingly, the constant data K₁₁, K₁₂, K₁₃, K₁₄, and K₁₅ are 1/2, 3/8,1/4, 1/8, and 0, respectively. By performing the similar calculation,the first conversion matrix K formed by constant data K_(ij) in thematrix of 18 rows by 20 columns may be obtained. The first conversionmatrix K is represented by Expression (22).

As described above, even in this embodiment, the element data P largerin number than those of detection data S may be configured by acalculation process simplified similarly to the first embodiment.

Furthermore, according to this embodiment, the plurality of terminals Tare disposed for one electrode ER and single detection data S isgenerated for each terminal T, and therefore, the number of electrodesER is smaller than the number of detection data S. Accordingly, thesensor unit 10B may be configured simpler.

Note that the present invention is not limited to the foregoingembodiments and includes various modifications.

Although a fixed value is used as an initial value of the dataconfiguration process to be repeatedly performed as an example in theforegoing embodiments, the present invention is not limited to this.

FIG. 29 is a flowchart for explaining a modification of a process ofconfiguring M pieces of element data P from N pieces of detection dataS.

In the flowchart of FIG. 7, when a first data configuration process(ST110) is performed, temporary values SA₁ to SA_(N) of detection dataare calculated by using the temporary values PA₁ to PA_(M) of theelement data obtained in step ST105 as initial values. However, as acalculation result is constant all the time independent from thedetection data S₁ to S_(N), the calculation may not be performed everytime one of the element data P₁ to P_(M) is configured. Therefore, inthe flowchart of the modification shown in FIG. 29, a calculation step(the first process) of calculating the temporary values SA₁ to SA_(N) ofthe detection data is omitted when the first data configuration process(ST110A) is performed.

Specifically, the element data configuration unit 22 does not performthe calculation process (the first process in ST200 of FIG. 8) ofcalculating the temporary values SA₁ to SA_(N) of the detection datawhen the first data configuration process is performed (ST110A), butobtains the temporary values SA₁ to SA_(N) of the detection data fromthe storage unit 30 or the like as initial values (ST105A). When asecond data configuration process (ST115) is performed, the element dataconfiguration unit 22 calculates the temporary values SA₁ to SA_(N) ofthe detection data based on the temporary values PA₁ to PA_(M) of theelement data corrected by the preceding data configuration process(ST110A) (the first process).

In this way, a processing speed may be improved by omitting thecalculation step (the first process) of calculating the temporary valuesSA₁ to SA_(N) of the detection data when the first data configurationprocess is performed (ST110A).

FIG. 30 is a flowchart for explaining another modification of a processof configuring M pieces of element data P from N pieces of detectiondata S.

Although estimation values are calculated as results of a dataconfiguration process performed a plurality of times by using results ofthe data configuration process performed twice in the foregoingembodiment, an error may be increased when a value of the detection dataS is small or the like. In this case, accuracy of definite values of theelement data P₁ to P_(M) may be enhanced by repeatedly performing thedata configuration process many times (L times) according to the processof the flowchart in FIG. 30. Step ST300 to step ST305 in the flowchartof FIG. 30 are the same as step ST100 to step ST105 shown in theflowchart of FIG. 7. The element data configuration unit 22 repeatedlyperforms the data configuration process (FIG. 8) L times in accordancewith the process from step ST310 to step ST325. The element dataconfiguration unit 22 obtains the temporary values PA₁ to PA_(M) of theelement data obtained by the data configuration process performed Ltimes as definite values of the element data P₁ to P_(M) (ST330).

1. An input device which inputs information corresponding to proximityof an object to an operation plane, the input device comprising: asensor unit configured to detect a degree of proximity of the object inone or more detection regions on the operation plane, generate one ormore pieces of detection data corresponding to a result of the detectionfor each detection region, and generate N pieces of detection data as awhole; and an element data configuration unit configured to configure,based on the N pieces of detection data, M pieces of element dataindicating degrees of proximity of the object in each of M sectionswhich virtually divide the operation plane, wherein M is a naturalnumber larger than N, each of the M sections has at least oneoverlapping portion which overlaps with the detection region, each ofthe M pieces of element data is a sum of partial element datadistributed to each of the N pieces of detection data in predeterminedrates, each of the N pieces of detection data is approximated to a sumof the partial element data individually distributed from each of the Mpieces of element data in the predetermined rates, and the element dataconfiguration unit calculates each of temporary values of the N piecesof detection data as sums of the partial element data distributed fromeach of temporary values of the M pieces of element data in thepredetermined rates and repeatedly performs a data configuration processof correcting the temporary values of the M pieces of element data atleast twice based on the N predetermined rates set for each of the Mpieces of element data so that the calculated temporary values of the Npieces of detection data are approximated to the N pieces of detectiondata, calculates, based on two temporary values obtained by the dataconfiguration process performed twice on each of the M pieces of elementdata, a coefficient having an absolute value which becomes small as adifference between the two temporary values in each of the element databecomes large, and calculates, for each of the M sections, a sum of avalue obtained by multiplying a difference between a first temporaryvalue of the element data obtained by the first data configurationprocess and a second temporary value of the element data obtained by thesecond data configuration process by the coefficient and the firsttemporary value as an estimation value of the element data obtained byrepeatedly performing the data configuration process.
 2. The inputdevice according to claim 1, wherein the element data configuration unitcalculates an evaluation value corresponding to a difference degreebetween the two temporary values of each of the M pieces of elementdata, and obtains a value of a predetermined function using theevaluation value as a variable as the coefficient.
 3. The input deviceaccording to claim 2, wherein the evaluation value is increased as thedifference degree of the two temporary values of each of the M pieces ofelement data is increased, and in the predetermined function, anabsolute value of a derivative in a range in which the evaluation valueis smaller than a threshold value is larger than an absolute value of aderivative in a range in which the evaluation value is larger than thethreshold value.
 4. The input device according to claim 2, wherein thedifference degree is an absolute value of a difference between the twotemporary values, and the element data configuration unit calculates theevaluation value according to a sum of the M difference degreescorresponding to the M pieces of element data.
 5. The input deviceaccording to claim 4, wherein the predetermined function is a linearfunction having a negative inclination.
 6. The input device according toclaim 5, wherein the evaluation value is increased as the differencedegree of the two temporary values of each of the M pieces of elementdata is increased, and in the predetermined function, an absolute valueof an inclination in a range in which the evaluation value is smallerthan a threshold value is larger than an absolute value of aninclination in a range in which the evaluation value is larger than thethreshold value.
 7. The input device according to claim 2, wherein theevaluation value is changed in accordance with the relative positionalrelationship between a plurality of objects approaching the operationplane.
 8. The input device according to claim 1, wherein the twotemporary values are the first and second temporary values.
 9. The inputdevice according to claim 1, wherein the first temporary values aretemporary values of the element data obtained by the first dataconfiguration process, and the second temporary values are temporaryvalues of the element data obtained by the second data configurationprocess.
 10. The input device according to claim 1, wherein the dataconfiguration process includes a first process of converting temporaryvalues of the M pieces of element data into temporary values of the Npieces of detection data based on the N predetermined rates set to eachof the M pieces of element data, a second process of calculating N firstcoefficients indicating magnifications by which temporary values of theN pieces of detection data are to be multiplied so that the temporaryvalues of the N pieces of detection data become equal to the N pieces ofdetection data, a third process of converting the N first coefficientsinto M second coefficients indicating magnifications by which the Mpieces of element data are to be multiplied based on the N predeterminedrates set to each of the M pieces of element data, and a fourth processof correcting the temporary values of the M pieces of element data basedon the M second coefficients.
 11. The input device according to claim10, wherein the element data configuration unit converts, in the firstprocess, a matrix having temporary values of the M pieces of elementdata as components into a matrix having temporary values of the N piecesof detection data as components based on a first conversion matrixincluding M×N components corresponding to the M pieces of element dataand the N pieces of detection data, one component corresponding to thepredetermined rate associated with the single partial element datadistributed to the single detection data from the single element data.12. The input device according to claim 10, wherein the element dataconfiguration unit converts, in the third process, a matrix having the Nfirst coefficients as components into a matrix having the M secondcoefficients as components based on a second conversion matrix includingM×N components corresponding to the M pieces of element data and the Npieces of detection data, one component corresponding to thepredetermined rate associated with the single partial element datadistributed to the single detection data from the single element data.13. The input device according to claim 10, wherein the element dataconfiguration unit omits the first process but performs the secondprocess using predetermined N initial values as temporary values of theN pieces of detection data in the first data configuration process. 14.The input device according to claim 10, wherein in the first dataconfiguration process, the element data configuration unit performs thefirst process using M initial values based on at least a group of Mpieces of element data which has been just configured as temporaryvalues of the M pieces of element data.
 15. The input device accordingto claim 1, wherein the sensor unit includes N electrodes formed in therespectively different detection regions, and an electrostaticcapacitance detection unit configured to generate detection datacorresponding to first electrostatic capacitances in portions between anobject approaching the operation plane and the electrodes for each ofthe N electrodes, the single partial element data is approximated to asecond electrostatic capacitance generated between an overlappingportion of the single electrode in the single section and the object,and the single element data is approximated to a third electrostaticcapacitance obtained by combining all the second electrostaticcapacitances in the single section.
 16. The input device according toclaim 15, wherein each of the predetermined rates has a valuecorresponding to a rate of an area of an overlapping portion of acorresponding one of the electrodes in a corresponding one of thesections to an area of overlapping portions of all the electrodes in thecorresponding one of the sections.
 17. The input device according toclaim 1, wherein the sensor unit includes a plurality of electrodeswhich are formed in the respectively different detection regions andwhich have N terminals as a whole, each of the electrodes having aplurality of terminals, and an electrostatic capacitance detection unitconfigured to input charges to be accumulated in portions between anobject approaching the operation plane and the electrodes from the Nterminals respectively and generate the detection data corresponding toelectrostatic capacitances between the object and the electrodes foreach of the N terminals based on the input charges, the electrostaticcapacitance detection unit simultaneously inputs the charges accumulatedin the single electrode from the plurality of terminals disposed in theelectrode, by the simultaneous input, partial charges accumulated inportions between an overlapping portion of the single electrode in thesingle section and the object are distributed to each of the pluralityof terminals as distribution charges in accordance with conductance in arange from the overlapping portion to the plurality of terminals, thesingle partial element data is approximated to the distribution chargedistributed to the single terminal by the simultaneous input, and thesingle element data is approximated to a combined charge obtained bycombining all the partial charges accumulated in the overlappingportions of all the electrodes in the single section.
 18. The inputdevice according to claim 17, wherein one of the predetermined rates hasa value corresponding to a rate of an area of an overlapping portion ofthe single electrode in the single section to an area of overlappingportions of all the electrodes in the single section, and a rate ofconductance in a range from one of the terminals in the single electrodeto the overlapping portion to conductance in a range from all theterminals in the single electrode to the overlapping portion.
 19. Anelement data configuration method which causes an input device includinga sensor unit which detects degrees of proximity of an object in aplurality of different detection regions on an operation plane andgenerates N pieces of detection data in accordance with a result of thedetection to configure M pieces of element data indicating degrees ofproximity of the object in each of M sections which virtually divide theoperation plane based on the N pieces of detection data, wherein M is anatural number larger than N, each of the M sections has at least oneoverlapping portion which overlaps with the detection region, each ofthe M pieces of element data is a sum of partial element datadistributed to each of the N pieces of detection data in predeterminedrates, each of the N pieces of detection data is approximated to a sumof the partial element data distributed from each of the M pieces ofelement data in the predetermined rates, the element data configurationmethod includes: calculating respective temporary values of the N piecesof detection data as sums of the partial element data distributed fromeach of temporary values of the M pieces of element data in thepredetermined rates and repeatedly performing a data configurationprocess of correcting the temporary values of the M pieces of elementdata at least twice based on the N predetermined rates set for each ofthe M pieces of element data so that the calculated temporary values ofthe N pieces of detection data approximate the N pieces of detectiondata; calculating a coefficient having an absolute value which becomessmaller as a difference between the two temporary values in each of theelement data becomes larger based on the two temporary values obtainedby the data configuration process performed twice for each of the Mpieces of element data; and calculating, for each of the M sections, asum of a value obtained by multiplying a difference between a firsttemporary value of the element data obtained by the first dataconfiguration step and a second temporary value of the element dataobtained by the second data configuration step by the coefficient andthe first temporary value as an estimation value of the element dataobtained by repeatedly performing the data configuration process.
 20. Aprogram that causes a computer to execute the element data configurationmethod set forth in claim 19.